By Topic

Aerospace and Electronic Systems, IEEE Transactions on

Issue 1 • Date Jan. 2000

Filter Results

Displaying Results 1 - 25 of 37
  • Comments on "Relationships between dilution of precision for point positioning and for relative positioning with GPS"

    Page(s): 315 - 316
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (75 KB)  

    While appreciating the works of R.O. Nielson (1997) and P.J.G. Teunissen (1998), we would like to give the exact relationship between dilution of precision for relative and absolute positioning. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Errata: incorrect figure in "JointStars and GMTI: Past, present and future"

    Page(s): 349
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (357 KB)  

    It has been brought to the attention of the authors that Fig. 9 in the above-named article [ibid., 35, 2 (Apr. 1999), 748??761] was incorrect. They had intended to show the Hughes Pave Mover Antenna System but inadvertently showed the Grumman Antenna System. The Hughes Antenna System is shown here. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Call for papers

    Page(s): 349
    Save to Project icon | Request Permissions | PDF file iconPDF (357 KB)  
    Freely Available from IEEE
  • Synthesis of automatic gain controllers for conical scan tracking radar

    Page(s): 302 - 309
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (600 KB)  

    The automatic gain control (AGC) of a conical scan tracking radar IF amplifier is designed using H synthesis. It is shown that this technique is particularly suited for this problem because of its loop shaping capabilities and because it can tackle particular frequencies effectively, providing a correct balance among closed-loop stability, fast response to echo changes, and rejection of frequencies other than the echo modulation. Two controllers are implemented and compared with a standard controller, showing significant improvement in system tracking View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Sensor registration using neural networks

    Page(s): 85 - 101
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1492 KB)  

    One of the major problems in multiple sensor surveillance systems is inadequate sensor registration. We propose a new approach to sensor registration based on layered neural networks. The nonparametric nature of this approach enables many different kinds of sensor biases to be solved. As part of the implementation we develop some modifications to the common network training algorithm to tackle the inherent randomness in all components of the training set View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On GPS positioning and integrity monitoring

    Page(s): 327 - 336
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB)  

    The paper reinvestigates the measurement model associated with Global Positioning System (GPS) signal processing. It is argued that the GPS positioning model is better formulated as a linear equation with errors in both the data matrix and measurement variables. Furthermore, depending on the nature of the measurement errors, the model is categorized into unstructured and structured perturbation cases. In the former, the total least squares method is proposed for position fixing and clock bias determination. In the latter, an iteration method is developed to search for the optimal solution. In addition to the position update, both the total least squares and optimization methods provide estimates of the model mismatch which leads to a measure of GPS receiver autonomous integrity monitoring. Two new GPS fault detection metrics are then proposed and discussed. The first integrity test statistic is the norm of the residual vector in the total least squares estimate. Statistical properties of this test statistic are obtained for integrity monitoring. The second metric is a two-dimensional vector that characterizes the norm of the residual vector and mismatch matrix, both are outcomes of the total least squares method or the optimization method. The positioning and integrity monitoring schemes are verified using simulated examples View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Noise covariances estimation for systems with bias states

    Page(s): 226 - 233
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB)  

    This paper presents a new approach to noise covariances estimation for a linear, time-invariant, stochastic system with constant but unknown bias states. The system is supposed to satisfy controllable/observable conditions without bias states. Based on a restructured data representation, the covariance of a new variable that consists of measurement vectors is expressed as a linear combination of unknown parameters. Noise covariances are then estimated by employing a recursive least-squares algorithm. The proposed method requires no a priori estimates of noise covariances, provides consistent estimates, and can also be applied when the relationship between bias states and other states is unknown. The method has been applied to strapdown inertial navigation system initial alignment. Simulation results indicate a satisfactory performance of the proposed method View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimization of point target tracking filters

    Page(s): 15 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (936 KB)  

    We review a powerful temporal-based algorithm, a triple temporal filter (TTF) with six input parameters, for detecting and tracking point targets in consecutive frame data acquired with staring infrared (IR) cameras. Using an extensive data set of locally acquired real-world data, we used an iterative optimization technique, the Simplex algorithm, to find an optimum set of input parameters for a given data set. Analysis of correlations among the optimum filter parameters based on a representative subset of our database led to two improved versions of the filter: one dedicated to noise-dominated scenes, the other to cloud clutter-dominated scenes. Additional correlations of filter parameters with measures of clutter severity and target velocity as well as simulations of filter responses to idealized targets reveal which features of the data determine the best choice of filter parameters. The performance characteristics of the filter is detailed by a few example scenes and metric plots of signal to clutter gains and signal to noise gains over the total database View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Validation and comparison of coordinated turn aircraft maneuver models

    Page(s): 250 - 259
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (692 KB)  

    A major challenge posed by aircraft tracking problems is the nondeterministic nature of an aircraft flight, due to the difficulty of predicting the pilot's actions. Accurate aircraft maneuver models are however highly desirable, particularly in air defense applications, to achieve accurate tracking and prediction. Through analysis of actual fighter aircraft trajectories and comparison with the Singer maneuver model, particularly in terms of prediction performance, coordinated turn (CT) aircraft maneuver models are presented, compared, and validated. A more general CT model is shown to better model actual trajectories than the classical CT model used in the literature View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Loran-C cycle identification in hard-limiting receivers

    Page(s): 290 - 297
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (684 KB)  

    A new technique is presented for use in hard-limiting receivers. It is based on the widely used analogue “half-cycle peak ratio” (HCPR) technique, from which it differs by being entirely digital; no additional analogue signal processing or other hardware is required. Drawing on recent advances, the new method makes decisions based on a large number of sample points in each Loran-C pulse, thereby increasing the resilience of the identification process in the presence of noise. Performance of the algorithm in the face of continuous-wave interference is equal to or better than that of other cycle-identification techniques View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic-constraints method in nonstationary hot-clutter cancellation. II. Unsupervised training applications

    Page(s): 132 - 150
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1520 KB)  

    For pt. I see ibid., vol. 34, pp. 1271-1292 (1998). This paper considers the use of “stochastically constrained” spatial and spatio-temporal adaptive processing in multimode nonstationary interference (“hot clutter”) mitigation for scenarios that do not allow access to a group of range cells that are free from the backscattered sea/terrain signal (“cold clutter”). Since supervised training methods for interference covariance matrix estimation using the cold-clutter-free ranges are inappropriate in this case, we introduce and analyze adaptive routines which can operate on range cells containing a mixture of hot and cold clutter and possible targets (unsupervised training samples). Theoretical and simulation results are complemented by surface-wave over-the-horizon data processing, recently collected during experimental trials in northern Australia View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Proof of CFAR by the use of the invariant test

    Page(s): 336 - 339
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    Many adaptive detectors regulate the detection threshold adaptively through an estimate of the clutter power level, which is formed by reference cell samples. This paper proves by the use of the invariant test that a large class of adaptive detectors possesses the constant false-alarm rate (CFAR) property when they satisfy certain weak conditions. The proof reveals the mechanism of this class of CFAR detectors and provides a general method of proving the CFAR property View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Highest density gates for target tracking

    Page(s): 47 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB)  

    The problem of forming validation regions or gates for new sensor measurements obtained when tracking targets in clutter is considered. Target dynamics and measurement characteristics are modeled with, possible non-Gaussianities or nonlinearities, so that some degree of approximation is usually required in the computation of the filtering densities for the target position and predictive densities for future measurements. Highest density gates (HDGs) are proposed as summaries of the predictive densities. These gates are constructed numerically, via simulation from the filtering density approximation. The algorithm results in gates that are “exact” (up to numerical accuracy) regardless of the approximation used for the filtering density. That is, given an approximation to the filtering density, the gating procedure accounts for all further nonlinearities and non-Gaussianities. Numerical example show that when the predictive density is markedly non-Gaussian, HDGs offer advantages over the more common rectangular and ellipsoidal gates View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Ground target tracking with variable structure IMM estimator

    Page(s): 26 - 46
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1792 KB)  

    In this paper we present the design of a Variable Structure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obtained from an airborne sensor. The targets are moving along a highway, with varying obscuration due to changing terrain conditions. In addition, the roads can branch, merge or cross-the scenario represents target convoys along a realistic road network with junctions, changing terrains, etc. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography, The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variable structure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, significantly improving performance and reducing computational load. Data association is handled using an assignment algorithm. The estimator is designed to handle a very large number of ground targets simultaneously. A simulated scenario consisting of over one hundred targets is used to illustrate the selection of design parameters and the operation of the tracker. Performance measures are presented to contrast the benefits of the VS-IMM estimator over the Kalman filter and the standard IMM estimator, The VS-IMM estimator is then combined with multidimensional assignment to gain “time-depth.” The additional benefit of using higher dimensional assignment algorithms for data association is also evaluated View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Communication system and operation for lunar probes under lunar surface

    Page(s): 151 - 162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1100 KB)  

    In the Japanese LUNAR-A mission, penetrators will be deployed to the Moon for global seismic measurement. The unique communication system between the subsurface probes under the lunar surface and the lunar orbiter is described. Radiowave propagation through a crater which is formed at the penetration is investigated by means of scaled measurements in a simulating environment. Acquisition and tracking sequence is optimized within limited power capacity of the probe to maximize contact time between the probe and the spacecraft View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Parameter extraction for the extended cantilever model of magnetic component windings

    Page(s): 260 - 266
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (624 KB)  

    The extended cantilever model (ECM) for transformer or inductor windings is convenient from the parameter extraction standpoint since, theoretically, each model parameter can be extracted from a single measurement of an open-circuit voltage or a short-circuit current. The impedance of the sensor used to measure a short-circuit current, however, makes the “short” less ideal, and it has been believed that each parameter in the ECM cannot be directly measured unless the impedance of the current sensor is negligible. It is shown that as long as the ECM parameters are reactive (inductive or capacitive) and the current sensor resistive, the current-sense resistance does not have to be restrictively small for the ECM parameters to be directly measurable. A linear, broadband formulation is also presented for extraction of the model admittances using current sensors with significant impedances View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Neural network directed Bayes decision rule for moving target classification

    Page(s): 176 - 188
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1008 KB)  

    In this paper, a new neural network directed Bayes decision rule is developed for target classification exploiting the dynamic behavior of the target. The system consists of a feature extractor, a neural network directed conditional probability generator and a novel sequential Bayes classifier. The velocity and curvature sequences extracted from each track are used as the primary features. Similar to hidden Markov model scheme, several hidden states are used to train the neural network, the output of which is the conditional probability of occurring the hidden states given the observations. These conditional probabilities are then used as the inputs to the sequential Bayes classifier to make the classification. The classification results are updated recursively whenever a new scan of data is received. Simulation results on multiscan images containing heavy clutter are presented to demonstrate the effectiveness of the proposed methods View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Interacting multiple model fixed-lag smoothing algorithm for Markovian switching systems

    Page(s): 243 - 250
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (564 KB)  

    We investigate a suboptimal approach to the fixed-lag smoothing problem for Markovian switching systems. A fixed-lag smoothing algorithm is developed by applying the basic Interacting Multiple Model (IMM) approach to a state-augmented system. The computational load is roughly d (the fixed lag) times beyond that of filtering for the original system. In addition, an algorithm that approximates the “fixed-lag” mode probabilities given measurements up to current time is proposed. The algorithm is illustrated via a target tracking simulation example where a significant improvement over the filtering algorithm is achieved at the cost of a time delay (i.e., data up to time k are used to produce the smoothed state estimate at time k-d where the fixed large d>0). the IMM fixed-lag smoothing performance for the given example is comparable to that of an existing IMM fixed-interval smoother. Compared with fixed-interval smoothers, the fixed-lag smoothers can be implemented in real-time with a small delay View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Background noise suppression for signal enhancement by novelty filtering

    Page(s): 102 - 113
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (920 KB)  

    The enhancement of weak signals in the presence of background and channel noise is necessary to design a robust automatic signal detection and recognition system. The autoassociative property of neural networks can be used to map the identifying characteristics of input source waveforms or their spectra. This paper is directed at the exploitation of such neural network properties for novelty filtering that improves the detection probability of weak signals by learning and subsequent subtraction of noise background from the input waveform. A neural-network-based preprocessor that learns to selectively filter out the background noise without significantly affecting the signal will be highly useful in solving practical signal enhancement problems. An analytical basis is established for the operation of neural-network-based novelty filters that enhance the signal detectability in the presence of noise background and channel noise View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Range and time-to-intercept estimation based solely upon the power measurements of a radiating source

    Page(s): 316 - 320
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB)  

    Range estimation based solely upon the received signal power measurements is possible for a specific set of conditions. Ordinarily the solution to this problem is not possible when the power of the signal at the source and the closing velocity are unknown. However, if the receiving platform modifies its velocity while sampling, the problem can be formulated with independent equations and solved. A time-to-intercept estimator based upon the sample principles is also presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Broadband passive acoustic technique for target motion parameter estimation

    Page(s): 163 - 175
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1040 KB)  

    A nonlinear least-squares method is formulated to estimate the motion parameters of a target whose broadband acoustic energy emissions are received by a ground-based array of sensors. This passive technique is applied to real acoustic sensor data recorded during the passage of a variety of ground vehicles past a planar cross array and its effectiveness verified by comparing the results with the actual values of the target motion parameters. The technique cam also be applied to airborne targets View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Observation of extended targets with antenna arrays

    Page(s): 297 - 302
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB)  

    Moments of the scattering function are a superb set of parameters representing an extended radar target. This set perfectly matches the adopted radar observation sequence (detection, position estimation, resolution, recognition and tracking). The problem of the moment estimation in radar systems with antenna arrays is considered View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Analytic track solutions with range-dependent errors

    Page(s): 343 - 348
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB)  

    Analytic solutions are presented for track covariance matrices for exoatmospheric (disturbance-free) tracking with measurement errors proportional to a power of range. Also discussed is the use of segmented trajectories for cases in which the range power and other tracking parameters are piecewise constant View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Effective filtering of target glint

    Page(s): 234 - 240
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (652 KB)  

    An effective filter structure is suggested for filtering of target glint in active homing engagements of a ship-to-ship missile. The proposed filter has decoupled range and angle channels so that it has a sound mathematical basis as well as computational efficiency as applied to the interacting multiple model algorithm. The proposed algorithm in conjunction with an impact angle control law is tested by a series of simulation runs and it is shown to have superior performance compared with the other filter structures View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • RLS-based predictor for latency compensation in DGPS

    Page(s): 339 - 343
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB)  

    Differential Global Positioning System (DGPS) is a technique that is frequently used to correct for selective availability (SA) induced ranging errors. However, long sampling periods and the time delay (latency) between the generation of corrections and their application by the user are a fundamental performance limitation on DGPS. A recursive least squares (RLS) based predictor is suggested to provide future values of SA for latency compensation in DGPS. The efficacy of the predictor is illustrated for different amounts of learning data and sampling rates through collected SA from operational GPS satellite View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Lance Kaplan
Army Research Laboratory