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Aerospace and Electronic Systems, IEEE Transactions on

Popular Articles (January 2015)

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  • 1. Decorrelated unbiased converted measurement Kalman filter

    Publication Year: 2014 , Page(s): 1431 - 1444
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3209 KB) |  | HTML iconHTML  

    Converted measurement tracking is a technique that filters in the coordinate system where the underlying process of interest is linear and Gaussian and requires the measurements to be nonlinearly transformed to fit. The goal of the transformation is to allow for tracking in the coordinate system that is most natural for describing system dynamics. There are two potential issues that arise when performing converted measurement tracking. The first is conversion bias that occurs when the measurement transformation introduces a bias in the expected value of the converted measurement. The second is estimation bias that occurs because the estimate of the converted measurement error covariance is correlated with the measurement noise, leading to a biased Kalman gain. First, previously proposed unbiased conversions are examined. Following this, the decorrelated unbiased converted measurement approach is presented. Results show that to overcome conversion bias and estimation bias, an unbiased measurement conversion should be employed that calculates the converted measurement error covariance using the predicted measurement. The conversion approaches are evaluated in tracking scenarios relevant to radar and sonar measurements. View full abstract»

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  • 2. Tapped-inductor filter assisted soft-switching PWM DC-DC power converter

    Publication Year: 2005 , Page(s): 174 - 180
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1947 KB) |  | HTML iconHTML  

    A novel high-frequency transformer linked full-bridge type soft-switching phase-shift pulsewidth modulated (PWM) controlled dc-dc power converter is presented, which can be used as a power conditioner for small-scale photovoltaic and fuel cell power generation systems as well as isolated boost dc-dc power converter for automotive ac power supply. In these applications with low-voltage large-current sources, the full-bridge circuit is the most attractive topology due to the possibility of using low-voltage high-performance metal-oxide-semiconductor field-effect transistor (MOSFET) and achieving high efficiency of the dc-dc power converter. A tapped-inductor filter including the freewheeling diode is newly implemented in the output stage of the full-bridge phase-shift PWM dc-dc converter to achieve soft-switching operation for the wide load variation range. Moreover, in the proposed converter circuit, the circulating current is effectively minimized without using additional resonant circuit and auxiliary power switching devices. The practical effectiveness of the proposed soft-switching dc-dc power converter was verified in laboratory level experiment with 1 kW 100 kHz breadboard setup using power MOSFETs. Actual efficiency of 94-97% was obtained for the wide duty cycle and load variation ranges. View full abstract»

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  • 3. Survey of maneuvering target tracking. Part I. Dynamic models

    Publication Year: 2003 , Page(s): 1333 - 1364
    Cited by:  Papers (333)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (881 KB) |  | HTML iconHTML  

    This is the first part of a comprehensive and up-to-date survey of the techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. It surveys various mathematical models of target motion/dynamics proposed for maneuvering target tracking, including 2D and 3D maneuver models as well as coordinate-uncoupled generic models for target motion. This survey emphasizes the underlying ideas and assumptions of the models. Interrelationships among models and insight to the pros and cons of models are provided. Some material presented here has not appeared elsewhere. View full abstract»

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  • 4. 3D interferometric ISAR imaging of noncooperative targets

    Publication Year: 2014 , Page(s): 3102 - 3114
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1979 KB) |  | HTML iconHTML  

    Inverse synthetic aperture radar (ISAR) images are frequently used in target classification and recognition applications. Nevertheless, the interpretation of ISAR images remains problematic for several reasons. One of these is the fact that the image plane cannot be defined by the user but instead depends on the target's own motions and on its relative position with respect to the radar. In order to overcome the problem of interpreting two-dimensional (2D) ISAR images, a method for three-dimensional (3D) reconstruction of moving targets is presented. This method is based on the use of a dual interferometric ISAR system. The interferometric phases measured from two orthogonal baselines are used to jointly estimate the target's effective rotation vector and the heights of the scattering centers with respect to the image plane. The scattering center extraction from the ISAR image is performed by applying a multichannel CLEAN technique. Finally, a 3D image of the moving target is reconstructed from the 3D spatial coordinates of the scattering centers. The effectiveness and robustness of the proposed algorithm is first proven theoretically and then tested against several radar-target scenarios as well as in the presence of noise. View full abstract»

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  • 5. Demonstration of cognitive radar for target localization under interference

    Publication Year: 2014 , Page(s): 2440 - 2455
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2497 KB) |  | HTML iconHTML  

    An ultrawideband (UWB) multiple input/multiple output (MIMO) cognitive radar has been developed and demonstrated for the first time. Field-programmable gate array (FPGA) is used for waveform-level computing, while waveform optimization is accomplished in CPU. Working as a closed loop, convex optimization is applied to jointly design (arbitrary) transmitted waveforms and the receiving filters in response to the varying wireless environment. Multiple targets localization in the presence of interference is demonstrated. Shown in the experiment, performance improvement is obvious in all interference patterns. View full abstract»

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  • 6. Simplified analysis of PWM converters using model of PWM switch. II. Discontinuous conduction mode

    Publication Year: 1990 , Page(s): 497 - 505
    Cited by:  Papers (135)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (677 KB)  

    For pt.I see ibid., vol.26, no.3, p.490-6 (1990). According to the method of state-space averaging, when a pulsewidth modulation (PWM) converter enters discontinuous conduction mode (DCM), the inductor current state is lost from the average model of the converter. It is shown that there is neither theoretical nor experimental justification for the disappearance of the inductor state as claimed by the method of state-space averaging. For example, when the model of the PWM switch in DCM is substituted in the buck, boost, or buck-boost converter while the inductor is left intact, the average model has two poles: the first pole fp1 agrees with the single pole of state-space averaging, while the second pole fp2 occurs in the range fp2Fs/π. It is shown that the right-half plane zeros present in the control-to-output transfer functions of the boost, buck-boost, and Cuk converters in continuous conduction mode are also present in discontinuous conduction mode View full abstract»

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  • 7. Active power management system for an unmanned aerial vehicle powered by solar cells, a fuel cell, and batteries

    Publication Year: 2014 , Page(s): 3167 - 3177
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2717 KB) |  | HTML iconHTML  

    200W class, low-speed, long-endurance unmanned aerial vehicle (UAV) that employs solar cells, a fuel cell, and a battery pack as its power sources is considered. This study applies an active power management method that directs each individual source to generate the appropriate power, depending on the power supply and demand, instead of the passive method in which the power sources irresponsibly generate power, depending on their characteristics. The power management system (PMS) under active management determines the power output from each source. The flight test of the UAV with a PMS onboard is conducted for 3.8 h. The active PMS verifies its own feasibility as it successfully keeps the power sources within their proper operational bounds and maintains a target state-of-charge of 45%, while responding to the various conditions associated with the power required. In addition, through a comparison of flight test results with a power simulation of the passive method, the usefulness, advantages, and disadvantages of an active power management method over a passive method are investigated. View full abstract»

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  • 8. Analysis of code phase estimation error from resolved first arrival path

    Publication Year: 2014 , Page(s): 2456 - 2467
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (665 KB) |  | HTML iconHTML  

    In multipath environments, a global navigation satellite system (GNSS) receiver can obtain the most correct code phase estimate from the resolved first arrival path, which is expected to have the smallest excess delay (ED). However, because of the limited performance of the code phase discriminator, multipath interference (MI), and noise, the code phase estimate can be different from that of the true first arrival path. In this paper, we derive the statistical ED distribution and power delay spectrum of GNSS multipath components based on exponential scatterer distribution model (ESDM). In parallel, we investigate the ED distributions of the first arrival path, MI, and noise to develop mathematical expressions for the code phase estimation error (CPEE) distribution for wide, narrow, and strobe correlators in various multipath channels. The mathematical models of CPEE distributions have good match with the ESDM-based CPEE distributions and the CPEE distributions obtained from Monte Carlo simulations using the International Telecommunications Union Recommendations Section recommendation P.681-7 channel model. This paper introduces one of the first theoretical analyses and models of the GNSS CPEE distributions, which can provide insights into the CPEE in multipath environments and are essential to develop algorithms against multipath distortion. View full abstract»

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  • 9. Numerical and experimental studies of target detection with MIMO radar

    Publication Year: 2014 , Page(s): 1569 - 1577
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2855 KB) |  | HTML iconHTML  

    Spatially diverse multiple-input multiple-output (MIMO) radar systems combine multistatic measurements of the target under view into a single detection algorithm and are thereby expected to alleviate the effects of fading on target radar cross sections (RCS) as the angle of observation is varied. Previous analytical studies of target detection for this case have shown that MIMO radar detection performance can exceed that of the corresponding phased array radar if both sufficient spatial diversity and signal-to-noise ratio (SNR) are achieved. These results have been based on a statistical model for the multistatic RCS of the target that is similar to the traditional Swerling models of the monostatic RCS. The degree to which these results are applicable to specific target geometries therefore remains uncertain. To address this issue, two studies of MIMO radar target detection incorporating realistic RCS properties for specific target geometries were performed. The first study utilized a numerical method to compute the multistatic RCS of a helicopter-like target observed at center frequency 200 MHz, while the second involved radar measurements of an unmanned aerial vehicle (UAV) target at 2.75 and 4.5 GHz. MIMO radar configurations having two transmitters and either three (for the radar measurements) or four (numerical simulations) receivers were used. In both cases, multistatic received fields were combined with regulated thermal noise levels in postprocessing to study target detection performance. Because in general the azimuthal orientation of a specific target with respect to the radar is uncertain, the detection performance results shown are averaged over the azimuthal orientation angle of the target. The average over target orientation can also be interpreted as similar to an average over “trials” of a statistical target description, enabling comparisons of field properties averaged over target orientation with similar ensemble averages from the - tatistical models of the literature. Although detection performance curves for the specific targets considered are not identical to those predicted analytically by the statistical target model, results for these targets confirm that the MIMO radar system can achieve enhanced detection performance as compared with the corresponding phased array radar system. View full abstract»

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  • 10. Simplified analysis of PWM converters using model of PWM switch. Continuous conduction mode

    Publication Year: 1990 , Page(s): 490 - 496
    Cited by:  Papers (295)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (600 KB)  

    A circuit-oriented approach to the analysis of pulsewidth modulation (PWM) converters is presented. This method relies on the identification of a three-terminal nonlinear device, called the PWM switch, which consists of only the active and passive switches in a PWM converter. Once the invariant properties of the PWM switch are determined, its average equivalent circuit model can be derived. This model is versatile enough to easily account for storage-time modulation of bipolar junction transistor(s) (BJTs); the DC- and small-signal characteristics of a large class of PWM converters can then be contained by a simply replacing the PWM switch with its equivalent circuit model. The methodology is very similar to linear amplifier circuit analysis, whereby the transistor is replaced by its equivalent circuit model View full abstract»

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  • 11. Maximum Power Point Tracking of Multiple Photovoltaic Arrays: A PSO Approach

    Publication Year: 2011 , Page(s): 367 - 380
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3871 KB) |  | HTML iconHTML  

    Multiple photovoltaic (PV) modules feeding a common load is the most common form of power distribution used in solar PV systems. In such systems, providing individual maximum power point tracking (MPPT) schemes for each of the PV modules increases the cost. Furthermore, its v-i characteristic exhibits multiple local maximum power points (MPPs) during partial shading, making it difficult to find the global MPP using conventional single-stage (CSS) tracking. To overcome this difficulty, the authors propose a novel MPPT algorithm by introducing a particle swarm optimization (PSO) technique. The proposed algorithm uses only one pair of sensors to control multiple PV arrays, thereby resulting in lower cost, higher overall efficiency, and simplicity with respect to its implementation. The validity of the proposed algorithm is demonstrated through experimental studies. In addition, a detailed performance comparison with conventional fixed voltage, hill climbing, and Fibonacci search MPPT schemes are presented. Algorithm robustness was verified for several complicated partial shading conditions, and in all cases this method took about 2 s to find the global MPP. View full abstract»

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  • 12. Adaptive single-frame superresolution for detecting closely spaced IR targets in clutter

    Publication Year: 2014 , Page(s): 2489 - 2499
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5512 KB) |  | HTML iconHTML  

    This paper addresses the problem of individually resolving very closely spaced infrared (IR) point targets in clutter, an important requirement in a variety of applications including air defense, where groups of targets may be operating in close formations, and astronomy, where stars can be closely spaced in angle as seen from the sensor's perspective. Novel linear and nonlinear (order statistic) adaptive noncoherent superresolution spatial-processing methods are introduced and employed to solve this problem using a single frame of IR data. View full abstract»

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  • 13. Simulation of a 6/4 switched reluctance motor based on Matlab/Simulink environment

    Publication Year: 2001 , Page(s): 989 - 1009
    Cited by:  Papers (80)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1240 KB) |  | HTML iconHTML  

    A Matlab/Simulink environment to simulate a 6/4-switched reluctance motor is described. From its linear model to the nonlinear model, its dynamics is described and discussed in detail. All simulations are completely documented by their block diagrams and corresponding special Matlab functions and parameters quickly develop its model to the reader. Based on the developed model, simulation studies are performed and compared with measured motor phase currents either for hysteresis and voltage control strategies, and the steady-state motor operation to validate the model View full abstract»

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  • 14. Adaptive beamforming for low-angle target tracking under multipath interference

    Publication Year: 2014 , Page(s): 2564 - 2577
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2656 KB) |  | HTML iconHTML  

    Angle of arrival estimation of a low-altitude target over the sea surface is a difficult problem due to the multipath coherent interference from the image target. We present a new monopulse technique utilizing an iterative interference cancellation algorithm based on the array antenna structure to overcome performance degradation. Our algorithm is compared with the maximum likelihood estimator, as well as with the existing algorithm employing the specular reflected error finding function. View full abstract»

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  • 15. Rapid Convergence Rate in Adaptive Arrays

    Publication Year: 1974 , Page(s): 853 - 863
    Cited by:  Papers (705)  |  Patents (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2270 KB)  

    In many applications, the practical usefulness of adaptive arrays is limited by their convergence rate. The adaptively controlled weights in these systems must change at a rate equal to or greater than the rate of change of the external noise field (e.g., due to scanning in a radar if step scan is not used). This convergence rate problem is most severe in adaptive systems with a large number of degrees of adaptivity and in situations where the eigenvalues of the noise covariance matrix are widely different. A direct method of adaptive weight computation, based on a sample covariance matrix of the noise field, has been found to provide very rapid convergence in all cases, i.e., independent of the eigenvalue distribution. A theory has been developed, based on earlier work by Goodman, which predicts the achievable convergence rate with this technique, and has been verified by simulation. View full abstract»

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  • 16. Target tracking in a collaborative sensor network

    Publication Year: 2014 , Page(s): 2694 - 2714
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1959 KB) |  | HTML iconHTML  

    In a collaborative sensor network (CSN), the conventional target tracking algorithms employed are Kalman filtering (KF) or extended Kalman filtering (EKF). However, these techniques have a presumed probability distribution of the system noise and prediction noise. They also need some a priori information that may be unavailable in some circumstances. Therefore, the system is not flexible for a complicated scenario. With the help of a machine learning technique called expert prediction (EP), a novel target tracking approach for CSNs is developed. This scheme makes use of the aforementioned EP in parameter estimation course for the target of interest, instead of exploiting the filtering method as typically found in available literature. This idea is further unfolded with comparisons regarding the CSN using Kalman filters, extended Kalman filters, and decentralized sigma-point information filters (DSPIFs). The new tracking algorithm is investigated with both linear and nonlinear prediction methods. Simulation results demonstrate that this proposed measure will deliver forecasting output with more precision because of the built-in multimodel mode among different experts, the learning ability, and the self-perfection characteristic. Not only does this performance occur in a more robust way than those of the existing approaches - particularly in the presence of heavy clutter, highly maneuvering targets, and/or multiple targets - but it simultaneously requires the least a priori information and imposes the least limitation on the observation model. View full abstract»

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  • 17. Survey of maneuvering target tracking. Part V. Multiple-model methods

    Publication Year: 2005 , Page(s): 1255 - 1321
    Cited by:  Papers (138)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1185 KB) |  | HTML iconHTML  

    This is the fifth part of a series of papers that provide a comprehensive survey of techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I and Part II deal with target motion models. Part III covers measurement models and associated techniques. Part IV is concerned with tracking techniques that are based on decisions regarding target maneuvers. This part surveys the multiple-model methods $the use of multiple models (and filters) simultaneously - which is the prevailing approach to maneuvering target tracking in recent years. The survey is presented in a structured way, centered around three generations of algorithms: autonomous, cooperating, and variable structure. It emphasizes the underpinning of each algorithm and covers various issues in algorithm design, application, and performance. View full abstract»

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  • 18. Kalman filtering with state equality constraints

    Publication Year: 2002 , Page(s): 128 - 136
    Cited by:  Papers (105)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (781 KB) |  | HTML iconHTML  

    Kalman filters are commonly used to estimate the states of a dynamic system. However, in the application of Kalman filters there is often known model or signal information that is either ignored or dealt with heuristically. For instance, constraints on state values (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. A rigorous analytic method of incorporating state equality constraints in the Kalman filter is developed. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraint surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a simple nonlinear vehicle tracking problem View full abstract»

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  • 19. Verification of a CubeSat via hardware-in-the-loop simulation

    Publication Year: 2014 , Page(s): 2807 - 2818
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1523 KB) |  | HTML iconHTML  

    This paper describes the hardware-in-the-loop (HIL) simulation methodology used for the verification of functional requirements of e-st @r-I CubeSat. The satellite's behavior is investigated via HIL simulation, and the results obtained are consistent with the expected values in any operative conditions. It is proven that HIL simulation is a valuable means for supporting the verification process of small satellites and may help reduce the time and cost of the development phase and increase mission reliability. View full abstract»

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  • 20. Multitarget Bayes filtering via first-order multitarget moments

    Publication Year: 2003 , Page(s): 1152 - 1178
    Cited by:  Papers (405)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (683 KB) |  | HTML iconHTML  

    The theoretically optimal approach to multisensor-multitarget detection, tracking, and identification is a suitable generalization of the recursive Bayes nonlinear filter. Even in single-target problems, this optimal filter is so computationally challenging that it must usually be approximated. Consequently, multitarget Bayes filtering will never be of practical interest without the development of drastic but principled approximation strategies. In single-target problems, the computationally fastest approximate filtering approach is the constant-gain Kalman filter. This filter propagates a first-order statistical moment - the posterior expectation - in the place of the posterior distribution. The purpose of this paper is to propose an analogous strategy for multitarget systems: propagation of a first-order statistical moment of the multitarget posterior. This moment, the probability hypothesis density (PHD), is the function whose integral in any region of state space is the expected number of targets in that region. We derive recursive Bayes filter equations for the PHD that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets. We also show that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense. View full abstract»

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  • 21. IM-filter for INS/GPS-integrated navigation system containing low-cost gyros

    Publication Year: 2014 , Page(s): 2619 - 2629
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1222 KB) |  | HTML iconHTML  

    This paper proposes a new interacting multiple (IM) filter containing simplified unscented Kalman filter (UKF) -based subfilters with different heading initializations for a low-performance inertial sensors-based inertial navigation system (INS)/global positioning system (GPS) -integrated navigation system tolerant toward large initial heading error. Since each individual subfilter of the IM filter is updated adaptively using the combined information of the estimates from the subfilters, it can converge into a true steady state irrespective of the initial heading of a vehicle containing the navigation system. Thereby the IM filter can provide a stable navigation solution. For the subfilters of the IM filter, a simplified UKF is presented. This has a mixed structure of the extended Kalman filter and UKF and has a lighter computational load than the UKF in the multirate INS/GPS integration. Also, simplified UKF-based subfilters for the INS/GPS-integrated navigation system are designed. Monte Carlo simulations are performed to validate the performance of the proposed IM filter, and an experiment is carried out to confirm the simulation results. View full abstract»

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  • 22. New chirp sequence radar waveform

    Publication Year: 2014 , Page(s): 2870 - 2877
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1017 KB) |  | HTML iconHTML  

    The general requirement in the automotive radar application is to measure the target range R and radial velocity vr simultaneously and unambiguously with high accuracy and resolution even in multitarget situations, which is a matter of the appropriate waveform design. Based on a single continuous wave chirp transmit signal, target range R and radial velocity vr cannot be measured in an unambiguous way. Therefore a so-called multiple frequency shift keying (MFSK) transmit signal was developed, which is applied to measure target range and radial velocity separately and simultaneously. In this case the radar measurement is based on a frequency and additionally on a phase measurement, which suffers from a lower estimation accuracy compared with a pure frequency measurement. This MFSK waveform can therefore be improved and outperformed by a chirp sequences waveform. Each chirp signal has in this case very short time duration Tchirp. Therefore the measured beat frequency fB is dominated by target range R and is less influenced by the radial velocity vr. The range and radial velocity estimation is based on two separate frequency measurements with high accuracy in both cases. Classical chirp sequence waveforms suffer from possible ambiguities in the velocity measurement. It is the objective of this paper to modify the classical chirp sequence to get an unambiguous velocity measurement even in multitarget situations. View full abstract»

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  • 23. GPS-based attitude determination for a spinning rocket

    Publication Year: 2014 , Page(s): 2654 - 2663
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3351 KB) |  | HTML iconHTML  

    An algorithm is developed for determining the attitude of a spinning sounding rocket. This algorithm is able to track global positioning system (GPS) signals with intermittent availability but with enough accuracy to yield phase observables for the precise, three-axis attitude determination of a nutating rocket. Raw, single-frequency GPS RF front-end data are processed by several filters to accomplish this task. First, a Levenberg-Marquardt algorithm (LMA) estimates GPS observables for multiple satellites by performing a least-squares fit to the accumulation outputs of a bank of correlators. These observables are then used as measurements in a Rauch-Tung-Striebel smoother that optimizes estimates of carrier phase, Doppler shift, and code phase. Finally, attitude determination is carried out by another batch filter that uses the single-differenced optimized carrier phase estimates between two antennas and an Euler dynamics model for the torque-free attitude motion of the spinning rocket. This second batch filter implements a combination of a substantially modified form of the LMA and the least-squares ambiguity decorrelation adjustment (LAMBDA) method. This design enables it to deal with integer ambiguities that change over long data gaps between times of carrier phase availability. The algorithm presented in this paper is applied to recorded RF data from a spinning sounding rocket mission to produce attitude quaternion and spin-rate estimates using a pair of antennas separated by a 0.3-m baseline. These results are confirmed by another set of quaternions and spin-rate vectors independently estimated from magnetometer and horizon crossing indicator data. Attitude precision on the order of several degrees has been demonstrated. View full abstract»

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  • 24. Position-Location Solutions by Taylor-Series Estimation

    Publication Year: 1976 , Page(s): 187 - 194
    Cited by:  Papers (339)  |  Patents (50)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1524 KB)  

    Taylor-series estimation gives a least-sum-squared-error solution to a set of simultaneous linearized algebraic equations. This method is useful in solving multimeasurement mixed-mode position-location problems typical of many navigational applications. While convergence is not proved, examples show that most problems do converge to the correct solution from reasonable initial guesses. The method also provides the statistical spread of the solution errors. View full abstract»

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  • 25. Multipath exploitation in through-the-wall radar imaging using sparse reconstruction

    Publication Year: 2014 , Page(s): 920 - 939
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2210 KB) |  | HTML iconHTML  

    Multipath exploitation and compressive sensing (CS) have both been applied independently to through-the-wall radar imaging (TWRI). Fast and efficient data acquisition is desired in scenarios where multipath effects cannot be neglected. Hence, we combine the two methods to achieve good image reconstruction in multipath environments from few spatial and frequency measurements. Ghost targets appear in the scene primarily due to specular reflections from interior walls and multiple reflections within the front wall. Assuming knowledge of the room geometry, we can invert the multipath model and eliminate ghosts by means of CS. We develop effective methods for the reconstruction of stationary scenes, which employ a group sparse CS approach. Additionally, we separate the target and wall contributions to the image by a sparse reconstruction approach joining wall and target models, which allows suppression of the ghosts and increased signal-to-clutter ratio (SCR) at the target locations. Effectiveness of the proposed approach is demonstrated using both simulated and real data. View full abstract»

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  • 26. Interacting multiple model methods in target tracking: a survey

    Publication Year: 1998 , Page(s): 103 - 123
    Cited by:  Papers (192)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2356 KB)  

    The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is its ability to estimate the state of a dynamic system with several behavior modes which can “switch” from one to another. In particular, the IMM estimator can be a self-adjusting variable-bandwidth filter, which makes it natural for tracking maneuvering targets. The importance of this approach is that it is the best compromise available currently-between complexity and performance: its computational requirements are nearly linear in the size of the problem (number of models) while its performance is almost the same as that of an algorithm with quadratic complexity. The objective of this work is to survey and put in perspective the existing IMM methods for target tracking problems. Special attention is given to the assumptions underlying each algorithm and its applicability to various situations View full abstract»

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  • 27. PCRLB for tracking in cluttered environments: measurement sequence conditioning approach

    Publication Year: 2006 , Page(s): 680 - 704
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4489 KB) |  | HTML iconHTML  

    We consider the problem of calculating the posterior Cramer-Rao lower bound (PCRLB) for tracking in cluttered domains in which there can be both missed detections and false alarms. We present a novel formulation of the PCRLB in which we initially determine a bound conditional on the sequence of measurements available. We then create an unconditional bound as a weighted average of these conditional PCRLBs. This new bound is proven to be less optimistic than the standard formulation of the PCRLB for cluttered environments recently developed (Zhang and Willett, 2001 and Hernandez et al., 2002) and will therefore better predict optimal estimator performance. At each stage, the conditional PCRLB must evaluate the effect of the uncertain measurements, and we extend previous work (Hernandez et al., 2002) to show that the measurement origin uncertainty manifests itself as a single information reduction factor (IRF) that is dependent on the number of measurements available. We also present some useful approximations when the false alarm rate is low. Simulations then consider the problems of 1) determining the CRLB for the point of impact of a ballistic missile, and 2) determining the PCRLB for tracking a nearly constant-velocity (NCV) target in a high clutter environment. In each case, we compare the new bound with the standard approach, and as expected the new CRLB/PCRLB can be seen to be less optimistic. Moreover, in case 1) we compare the new CRLB with a heuristic bound specially constructed for this problem, and a maximum likelihood estimator (MLC). The new bound both compares favorably with the heuristic bound, and shows close agreement with the performance of the MLE. The new bound is therefore an accurate predictor of filter performance in this case. In example 2) we demonstrate some interesting features of the new theory. Of particular interest we determine both precisely when the new bound will be significantly greater than the standard bound and when the two bounds will be virtually identical. This is useful in determining when the new approach, with its greater computational burden, should be preferred to the established approach. We conclude that the novel PCRLB formulation introduced herein represents an exciting development in the determination of RMSE p- erformance bounds in cluttered environments. View full abstract»

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  • 28. An Algebraic Solution of the GPS Equations

    Publication Year: 1985 , Page(s): 56 - 59
    Cited by:  Papers (74)  |  Patents (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (775 KB)  

    The global positioning system (GPS) equations are usually solved with an application of Newton's method or a variant thereof: Xn+1 = xn + H-1(t - f(xn)). (1) Here x is a vector comprising the user position coordinates together with clock offset, t is a vector of tour pseudorange measurements, and H is a measurement matrix of partial derivatives H = fx· In fact the first fix of a Kalman filter provides a solution of this type. If more than four pseudoranges are available for extended batch processing, H-1 may be replaced by a generalized inverse (HTWH)-1HTW, where W is a positive definite weighting matrix (usually taken to be the inverse of the measurement covariance matrix). This paper introduces a new method of solution that is algebraic and noniterative in nature, computationally efficient and numerically stable, admits extended batch processing, improves accuracy in bad geometric dilution of precision (GDOP) situations, and allows a "cold start" in deep space applications. View full abstract»

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  • 29. Survey of Maneuvering Target Tracking. Part II: Motion Models of Ballistic and Space Targets

    Publication Year: 2010 , Page(s): 96 - 119
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2566 KB) |  | HTML iconHTML  

    This paper is the second part in a series that provides a comprehensive survey of maneuvering target tracking without addressing the so-called measurement-origin uncertainty. It surveys motion models of ballistic targets used for target tracking. Models for all three phases (i.e., boost, coast, and reentry) of motion are covered. View full abstract»

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  • 30. A Vision-Based Automatic Safe Landing-Site Detection System

    Publication Year: 2013 , Page(s): 294 - 311
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (17786 KB) |  | HTML iconHTML  

    An automatic safe landing-site detection system is proposed for aircraft emergency landing based on visible information acquired by aircraft-mounted cameras. Emergency landing is an unplanned event in response to emergency situations. If, as is usually the case, there is no airstrip or airfield that can be reached by the unpowered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing-site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing-site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on external environmental factors that can impair human vision and on the pilot's flight experience, which can vary significantly among pilots. Therefore, we propose a robust, reliable, and efficient detection system that is expected to alleviate the negative impact of these factors. We focus on the detection mechanism of the proposed system and assume that image enhancement for increased visibility and image stitching for a larger field-of-view (FOV) have already been performed on the terrain images acquired by aircraft-mounted cameras. Specifically, we first propose a hierarchical elastic horizon detection algorithm to identify the ground in the image. Then, the terrain image is divided into nonoverlapping blocks, which are clustered according to a "roughness" measure. The adjacent smooth blocks are merged to form potential landing-sites, whose dimensions are measured with principal component analysis and geometric transformations. If the dimensions of a candidate region exceed the minimum requirement for safe landing, the potential landing-site is considered a safe candidate and is highlighted on the human machine interface. At the end the pilot makes the final decision by confirming one of the candidates, and also by considering other factors such as wind speed and wind direction, etc. Preliminary experimental results show the feasibili- y of the proposed system. View full abstract»

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  • 31. Efficient target detection using an adaptive compressive imager

    Publication Year: 2014 , Page(s): 2528 - 2540
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1296 KB) |  | HTML iconHTML  

    The goal of a target detection system is to determine the location of potential targets in the field of view of the sensor. Traditionally, this is done using high-quality images from a conventional imager. For wide-field-of-view scenarios, this can pose a challenge for both data acquisition and system bandwidth. In this paper, we discuss a compressive sensing technique for target detection that dramatically reduces the number of measurements that is required to perform the task, as compared with the number of pixels in conventional images. This, in turn, can reduce the data rate from the sensor electronics, and along with it, the cost, complexity, and the bandwidth requirements of the system. Specifically, we discuss a two-stage approach that, first, adaptively searches a large area using shift-invariant masks to determine the locations of potential targets (i.e., the regions of interest) and then revisits each location to discriminate between target and clutter using a different set of specialized masks.We show that the overall process is not only highly efficient (i.e., dramatically reduces the number of measurements as compared with the number of pixels) but does so without appreciable loss in target detection performance. View full abstract»

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  • 32. Decoupled ISAR imaging using RSFW based on twice compressed sensing

    Publication Year: 2014 , Page(s): 3195 - 3211
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2806 KB) |  | HTML iconHTML  

    Random stepped-frequency radar without delay-Doppler coupling can suppress the range ambiguity and become less sensitive to electronic countermeasures. Considering its inherent randomness, this paper focuses on sidelobe reduction in inverse synthetic aperture radar imaging for sparse target scenes based on the compressed sensing (CS) theory. First, precise motion compensation and a high-resolution range profile (HRRP) with a low sidelobe are simultaneously achieved by the CS scheme for each train containing fewer pulses. Then, we analyze the disadvantages of conventional cross-range compression algorithms, which cannot guarantee high-quality focusing performance because there may be some false HRRPs caused by the uncertainty of the CS theory or some other factors. Finally, the modified correlation coefficient is defined to discard a large percentage of those uncorrelated HRRPs and the cross-range resolution is achieved by using the CS theory again. The validity of this decoupled imaging algorithm is demonstrated by some simulation and experimental results, which indicate that the approach is capable of precise estimation of scattering centers and effective suppression of a high sidelobe. View full abstract»

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  • 33. Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion

    Publication Year: 2001 , Page(s): 273 - 279
    Cited by:  Papers (109)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (508 KB) |  | HTML iconHTML  

    Currently there exist two commonly used measurement fusion methods for Kalman-filter-based multisensor data fusion. The first (Method I) simply merges the multisensor data through the observation vector of the Kalman filter, whereas the second (Method II) combines the multisensor data based on a minimum-mean-square-error criterion. This paper, based on an analysis of the fused state estimate covariances of the two measurement fusion methods, shows that the two measurement fusion methods are functionally equivalent if the sensors used for data fusion, with different and independent noise characteristics, have identical measurement matrices. Also presented are simulation results on state estimation using the two measurement fusion methods, followed by the analysis of the computational advantages of each method View full abstract»

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  • 34. Singular perturbationlike approach to compensation of actuator dynamics effect in missile control

    Publication Year: 2014 , Page(s): 2417 - 2439
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2251 KB) |  | HTML iconHTML  

    Our recently developed nonlinear autopilot controller can make the input-output (I/O) dynamic characteristics of the nonlinear bank-to-turn (BTT) missile system linear and independent of flight conditions. However, relatively slow actuator dynamics can degrade its performance significantly. The proposed compensation method can nearly eliminate the effect of slow actuator dynamics while maintaining the desired linear I/O dynamic characteristics. It considers fully the nonminimum-phase nonlinear BTT missile dynamics but requires no differentiations of noisy variables, unlike other existing control methods. View full abstract»

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  • 35. Direct Kalman filtering approach for GPS/INS integration

    Publication Year: 2002 , Page(s): 687 - 693
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    We present a novel Kalman filtering approach for GPS/INS integration. In the approach, GPS and INS nonlinearities are preprocessed prior to a Kalman filter. The GPS preprocessed data are taken as measurement input, while the INS preprocessed data are taken as additional information for the state prediction of the Kalman filter. The advantage of this approach, over the well-studied (extended) Kalman filtering approaches is that a simple and linear Kalman filter can be implemented to achieve significant computation saving with very competitive performance figures View full abstract»

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  • 36. A low complexity parameter estimation technique for LFMCW signals

    Publication Year: 2014 , Page(s): 2554 - 2563
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1022 KB) |  | HTML iconHTML  

    Linear frequency modulated continuous waveform (LFMCW) is a modulation technique commonly used in bistatic radar systems due to its constant power and excellent range resolution. In this paper, we propose a method for estimating the parameters of an unknown LFMCW signal embedded in noise. The parameters to be estimated include sweep length, time offset, bandwidth, and center frequency. Unlike existing LFMCW parameter estimation techniques, which estimate the parameters jointly, the proposed method estimates the unknown parameters in a sequential order. As a result, it has a very low computational complexity. In addition, it does not require any prior information about the unknown parameters. This property together with its low complexity makes it a suitable candidate for real-time applications. View full abstract»

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  • 37. Radar code design for detection of moving targets

    Publication Year: 2014 , Page(s): 2762 - 2778
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1826 KB) |  | HTML iconHTML  

    In this paper, we study the problem of pulsed-radar transmit code design for detection of moving targets in the presence of signal-dependent clutter. For unknown target Doppler shift, the optimal detector does not lead to a closed-form expression. Therefore, we resort to average and worst case performance metrics of the optimal detector for code design. We propose several algorithms under two novel frameworks to solve highly nonconvex design problems.We also consider low peak-to-average-power ratio (PAR) code design. View full abstract»

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  • 38. Subarray-based frequency diverse array radar for target range-angle estimation

    Publication Year: 2014 , Page(s): 3057 - 3067
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1429 KB) |  | HTML iconHTML  

    Phased-array is widely used in communication, radar, and navigation systems, but the beam steering is fixed in an angle for all range cells. Frequency diverse array (FDA) provides a range-dependent beamforming, but it cannot estimate directly both the range and angle of a target. This paper proposes a subarray-based FDA radar, with an aim to localize the target in the range-angle domain.We divide the whole FDA array into two subarrays, which employ two different frequency increments. In doing so, the target's range and angle are estimated directly from the transmit-receive beamforming output peak. The estimation performance is examined by analyzing the minimum mean variance square error (MMSE) and the Cramer-Rao lower bound (CRLB) versus signal-to-noise ratio (SNR). The corresponding transmit-receive beampattern and signal-to-interference plus noise ratio (SINR) are also formalized. Moreover, the CRLB can be used to optimally design the frequency increments. The effectiveness is verified by simulation results. View full abstract»

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  • 39. Compressed sensing radar amid noise and clutter using interference covariance information

    Publication Year: 2014 , Page(s): 887 - 897
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1454 KB) |  | HTML iconHTML  

    Adaptive radar processing has been shown to be useful in downward-looking radars that must detect moving targets in the midst of strong clutter returns. Compressed sensing has found applications in radar problems but has not been comprehensively studied with respect to clutter and other structured interference. The performance of compressed sensing radar techniques in the presence of clutter is explored herein and compared to existing adaptive radar processing methods, including Space-Time Adaptive Processing (STAP), via Monte Carlo exploration of target detection performance. Finally, we propose extensions to standard ¿1 optimization techniques to account for known interference covariance matrix statistics. These extensions outperform current compressed sensing techniques, outperform the fully sampled, nonadaptive matched filter estimate, and approach the performance level of the fully sampled STAP estimate. However, similar detection performance can be achieved at lower computational cost by applying a linear filter using the same covariance information. View full abstract»

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  • 40. Direction finding algorithms based on joint iterative subspace optimization

    Publication Year: 2014 , Page(s): 2541 - 2553
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1399 KB) |  | HTML iconHTML  

    In this paper, a reduced-rank scheme with joint iterative optimization is presented for direction of arrival estimation. A rank-reduction matrix and an auxiliary reduced-rank parameter vector are jointly optimized to calculate the output power with respect to each scanning angle. Subspace algorithms to estimate the rank-reduction matrix and the auxiliary vector are proposed. Simulations are performed to show that the proposed algorithms achieve enhanced performance over existing algorithms in the studied scenarios. View full abstract»

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  • 41. Box-particle probability hypothesis density filtering

    Publication Year: 2014 , Page(s): 1660 - 1672
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1560 KB) |  | HTML iconHTML  

    This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small number of box-particles makes this approach attractive for distributed inference, especially when particles have to be shared over networks. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes methods from the field of interval analysis. The theoretical derivation of the box-PHD filter is presented followed by a comparative analysis with a standard sequential Monte Carlo (SMC) version of the PHD filter. To measure the performance objectively three measures are used: inclusion, volume, and the optimum subpattern assignment (OSPA) metric. Our studies suggest that the box-PHD filter reaches similar accuracy results, like an SMC-PHD filter but with considerably less computational costs. Furthermore, we can show that in the presence of strongly biased measurement the box-PHD filter even outperforms the classical SMC-PHD filter. View full abstract»

    Open Access
  • 42. Detection with Distributed Sensors

    Publication Year: 1981 , Page(s): 501 - 510
    Cited by:  Papers (362)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2026 KB)  

    The extension of classical detection theory to the case of distributed sensors is discussed, based on the theory of statistical hypothesis testing. The development is based on the formulation of a decentralized or team hypothesis testing problem. Theoretical results concerning the form of the optimal decision rule, examples, application to data fusion, and open problems are presented. View full abstract»

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  • 43. MIMO adaptive beamforming for nonseparable multipath clutter mitigation

    Publication Year: 2014 , Page(s): 2604 - 2618
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2119 KB) |  | HTML iconHTML  

    The performance of ground-moving target indicator radars is often degraded in complex terrain by multipath spread-Doppler clutter. Multiple-input, multiple-output (MIMO) beamforming with limited training data has been previously proposed with separable transmit and receive weights appropriate for discrete multipath scenarios. In this paper, partially adaptive MIMO beamforming is presented for suppression of a nonseparable continuum of multipath clutter with limited training data. Simulation results for a forward-looking vehicle-mounted radar in a simplified urban environment are described. View full abstract»

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  • 44. Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets

    Publication Year: 1970 , Page(s): 473 - 483
    Cited by:  Papers (312)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2521 KB)  

    The majority of tactical weapons systems require that manned maneuverable vehicles, such as aircraft, ships, and submarines, be tracked accurately. An optimal Kalman filter has been derived for this purpose using a target model that is simple to implement and that represents closely the motions of maneuvering targets. Using this filter, parametric tracking accuracy data have been generated as a function of target maneuver characteristics, sensor observation noise, and data rate and that permits rapid a priori estimates of tracking performance to be made when maneuvering targets are to be tracked by sensors providing any combination of range, bearing, and elevation measurements. View full abstract»

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  • 45. Power tracking for nonlinear PV sources with coupled inductor SEPIC converter

    Publication Year: 2005 , Page(s): 1019 - 1029
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (451 KB) |  | HTML iconHTML  

    The photovoltaic (PV) generator exhibits a nonlinear i-v characteristic and its maximum power (MP) point varies with solar insolation. In this paper, a V2-based MP point tracking (MPPT) scheme is developed using a buck-boost transformation topology. Although several buck-boost transformation topologies are available we have considered here a coupled inductor SEPIC converter for experimentation. To achieve almost ripple-free array current we have used ripple steering phenomena with the help of integrated inductor. This integrated inductor not only reduces the magnetic core requirements but also improves converter performance. Mathematical models are formulated and tracking algorithm is evolved. A combined PV system simulation model is developed in the SIMULINK. For a given solar insolation, the tracking algorithm changes the duty ratio of the converter such that the solar cell array (SCA) voltage equals the voltage corresponding to the MP point. This is done by the tracking algorithm, which mainly computes the power proportional to square of terminal voltage and changes the duty ratio of the converter so that this power is maximum. The proposed algorithm is implemented in real-time with the help of Analog Device ADMC-401 DSP evaluation module. The tracking program is developed to perform experimental investigations using analog-to-digital converter (ADC) interrupt. Using this processor we are able to track the MP within 200 ms. The proposed peak power tracking effectiveness is demonstrated through simulation and experimental results. View full abstract»

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  • 46. Adaptive beamforming with compressed sensing for sparse receiving array

    Publication Year: 2014 , Page(s): 823 - 833
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1898 KB) |  | HTML iconHTML  

    An adaptive digital beamforming technique with compressed sensing (CS) for sparse receiving arrays is proposed. Because of the angle sparseness of arriving signals, CS theory can be adopted to sample receiving signals. Then, receiving signals from absent elements on the antenna aperture can be reconstructed by using CS method. Adaptive digital beamforming algorithms are adopted to form antenna beam, whose main lobe is steered to the desired direction and nulls steered to the directions of interference. View full abstract»

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  • 47. Sensor selection for nonlinear systems in large sensor networks

    Publication Year: 2014 , Page(s): 2664 - 2678
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (724 KB) |  | HTML iconHTML  

    In this paper, we consider multistage look-ahead sensor selection problems for nonlinear dynamic systems such as radar target tracking systems. We investigate the problem for large sensor networks for both independent and dependent Gaussian measurement noises in the presence of temporally separable as well as inseparable constraints, e.g., energy constraints. First, when the measurement noises are uncorrelated between sensors, we derive the optimal solution for sensor selection when the constraints are temporally separable. When constraints are temporally inseparable, we can obtain near-optimal solutions by relaxing the nonconvex problem formulation to a linear programming problem so that the sensor selection problem for a large sensor network can be solved in a computationally efficient manner. For illustration, a radar target tracking problem is considered where it is shown that the new method presented for nonlinear dynamic systems performs better than the method based on linearizing the nonlinear equations and using previous sensor selection methods for large sensor networks. Finally, when the measurement noises are correlated between the sensors, the sensor selection problem with temporally inseparable constraints can be relaxed to a Boolean quadratic programming problem,,which can be efficiently solved by a Gaussian randomization procedure along with solving a semidefinite programming problem. Numerical examples show that the proposed method that includes consideration of dependence performs much better than the method that ignores dependence of noises. View full abstract»

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  • 48. Covariance matrix estimation errors and diagonal loading in adaptive arrays

    Publication Year: 1988 , Page(s): 397 - 401
    Cited by:  Papers (260)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    Simulations were used to investigate the effect of covariance matrix sample size on the system performance of adaptive arrays using the sample matrix inversion (SMI) algorithm. Inadequate estimation of the covariance matrix results in adapted antenna patterns with high sidelobes and distorted mainbeams. A technique to reduce these effects by modifying the covariance matrix estimate is described from the point of view of eigenvector decomposition. This diagonal loading technique reduces the system nulling capability against low-level interference, but parametric studies show that it is an effective approach in many situations View full abstract»

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  • 49. Low-Frequency Characterization of Switched dc-dc Converters

    Publication Year: 1973 , Page(s): 376 - 385
    Cited by:  Papers (163)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2079 KB)  

    Averaging techniques are developed to represent buck, boost, and buck-boost types of switched dc-dc converters by approximate continuous models. Simple analytical expressions in terms of the circuit components are derived for the characteristic transient and frequency responses of time-average(continuous) power-stage models for use in designing and understanding the behavior of corresponding switched power stages. Novel conclusions include the dependence of effective circuit component values upon switch duty ratio and the existence of a real positive zero in certain transfer functions. Responses from analog computer simulations of the switched and averaged powerstages agree well and, in turn, confirm the analytic predictions. High-order systems can be analyzed by the averaging technique without a commensurate increase in complexity. View full abstract»

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  • 50. Detection performance of spatial-frequency diversity MIMO radar

    Publication Year: 2014 , Page(s): 3137 - 3155
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2694 KB) |  | HTML iconHTML  

    For spatial-frequency diversity radar, diversity channels may receive partially correlated target returns and channel signal-to-noise ratios (SNRs) may be different. For six typical scenarios of diversity radar, we design detection algorithms and analyze their detection performances in theory and via numerical results. It is shown that the detectors considering target correlation and channel SNR distribution can improve the detection performance of diversity radar. Whether certain channel SNRs can achieve a higher optimal detection probability than another depends on total channel SNR and false alarm rate. View full abstract»

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Aims & Scope

IEEE Transactions on Aerospace and Electronic Systems focuses on the equipment, procedures, and techniques applicable to the organization, installation, and operation of functional systems designed to meet the high performance requirements of earth and space systems.

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Editor-in-Chief
Lance Kaplan
Army Research Laboratory