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Aerospace and Electronic Systems, IEEE Transactions on

Issue 2 • Date April 2002

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Displaying Results 1 - 25 of 33
  • Homodyned-K fluctuation model

    Publication Year: 2002 , Page(s): 527 - 542
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1857 KB) |  | HTML iconHTML  

    The statistics of the matched filter output are examined for the case of a nonfluctuating target in K-type clutter. The resulting "homodyned-K" backscatter model is a generalization of the classic Rayleigh-Rice model and has applications in radar, sonar, optics, and ultrasonic medical imaging. This paper presents exact and asymptotic equations for the probability density function, survival function, moments, and parameter estimation. The exact equations are expressed as infinite series. Also provided are proof of the series' convergence and guidance for their numerical computation. Examples illustrating the model's application to radar and sonar are presented using electromagnetic and acoustic backscatter data. View full abstract»

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  • Track association and track fusion with nondeterministic target dynamics

    Publication Year: 2002 , Page(s): 659 - 668
    Cited by:  Papers (38)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (517 KB) |  | HTML iconHTML  

    Representative track fusion algorithms and track association metrics are quantitatively compared using a simple linear-Gaussian-Poisson model, under various degrees of nondeterministicity of the target dynamics, i.e., process noises, and of the initial condition uncertainty. Track fusion algorithms are compared using an analytical method, while track association metrics are evaluated by Monte Carlo simulations. View full abstract»

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  • 2001 Pioneer Award

    Publication Year: 2002 , Page(s): 721 - 722
    Save to Project icon | Request Permissions | PDF file iconPDF (317 KB)  
    Freely Available from IEEE
  • The Pioneer Award

    Publication Year: 2002 , Page(s): 734 - 735
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    Freely Available from IEEE
  • Smart flight control surfaces with microelectromechanical systems

    Publication Year: 2002 , Page(s): 543 - 552
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (992 KB) |  | HTML iconHTML  

    Pitch, roll, and yaw moments can be developed by deflecting and changing the geometry of control surfaces. In this paper, smart flight control surfaces are designed using multi-node microelectromechanical systems (MEMS) to displace control surfaces and change the surface geometry. These MEMS augment translational motion microstructures (actuators-sensors), controlling/signal processing integrated circuits (ICs), radiating energy devices and antennas. The desired pitch, roll, and yaw moments are produced, drag can be reduced, and unsteady aerodynamic flows are controlled by smart flight control surfaces. That is, we achieve aerodynamic moment and active flow control capabilities. The major objective here is to report fundamental and applied research in design of smart flight control surfaces with MEMS-based actuator-sensor-IC arrays controlled by hierarchical distributed systems. We demonstrate the feasibility and effectiveness of the application of smart flight control surfaces for coordinated longitudinal and lateral vehicle control View full abstract»

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  • Multicarrier radar signal - pulse train and CW

    Publication Year: 2002 , Page(s): 707 - 720
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1185 KB) |  | HTML iconHTML  

    A multicarrier complementary phase-coded (MCPC) radar signal employs N subcarriers simultaneously. The subcarriers are phase modulated by N different sequences that constitute a complementary set. The subcarriers are frequency-separated by the inverse of the duration of a phase element tb. An N×M MCPC pulse achieves pulse compression ratio of NM. When an N×M MCPC signal is used in a coherent train of N pulses (e.g., in order to allow Doppler processing), it is advantageous to use pulse diversity. Each pulse is constructed using a different cyclic frequency shift of the first pulse. Such pulse diversity eliminates recurrent lobes at multiples of the pulse repetition interval. The constant volume property of the ambiguity function is maintained by shifting volume from the recurrent lobes to the sidelobe pedestal strips. However, if the sequence ordering along frequencies in the N pulses are arranged to create a complementary set in each frequency as well as in each pulse, the sidelobe level around the main autocorrelation lobe is dramatically reduced. Preferred MCPC coding for CW mode (contiguous MCPC pulses) and their delay-Doppler response are also discussed View full abstract»

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  • Quantitative SNR analysis for ISAR imaging using joint time-frequency analysis-Short time Fourier transform

    Publication Year: 2002 , Page(s): 649 - 659
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1793 KB) |  | HTML iconHTML  

    V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging View full abstract»

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  • Accuracy performance of star trackers - a tutorial

    Publication Year: 2002 , Page(s): 587 - 599
    Cited by:  Papers (42)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1108 KB) |  | HTML iconHTML  

    An autonomous star tracker is an avionics instrument used to provide the absolute 3-axis attitude of a spacecraft utilizing star observations. It consists of an electronic camera and associated processing electronics. The processor has the capability to perform star identification utilizing an internal star catalog stored in firmware and to calculate the attitude quaternion autonomously. Relevant parameters and characteristics of an autonomous star tracker are discussed in detail View full abstract»

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  • Three-dimensional midcourse guidance using neural networks for interception of ballistic targets

    Publication Year: 2002 , Page(s): 404 - 414
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (868 KB) |  | HTML iconHTML  

    A suboptimal midcourse guidance law is obtained for interception of free-fall targets in the three-dimensional (3D) space. Neural networks are used to approximate the optimal feedback strategy suitable for real-time implementation. The fact that the optimal trajectory in the 3D space does not deviate much from a vertical plane justifies the use of the two-dimensional (2D) neural network method previously studied. To regulate the lateral errors in the missile motion produced by the prediction error of the intercept point, the method of feedback linearization is employed. Computer simulations confirm the superiority of the proposed scheme over linear quadratic regulator guidance and proportional navigation guidance as well as its approximating capability of the optimal trajectory in the 3D space View full abstract»

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  • MAP estimation of target manoeuvre sequence with the expectation-maximization algorithm

    Publication Year: 2002 , Page(s): 367 - 377
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (852 KB) |  | HTML iconHTML  

    Two algorithms are derived for the problem of tracking a manoeuvring target based on a sequence of noisy measurements of the state. Manoeuvres are modeled as unknown input (acceleration) terms entering linearly into the state equation and chosen from a discrete set. The expectation maximization (EM) algorithm is first applied, resulting in a multi-pass estimator of the MAP sequence of inputs. The expectation step for each pass involves computation of state estimates in a bank of Kalman smoothers tuned to the possible manoeuvre sequences. The maximization computation is efficiently implemented using the Viterbi algorithm. A second, recursive estimator is then derived using a modified EM-type cost function. To obtain a dynamic programming recursion, the target state is assumed to satisfy a Markov property with respect to the manoeuvre sequence. This results in a recursive but suboptimal estimator implementable on a Viterbi trellis. The transition costs of the latter algorithm, which depend on filtered estimates of the state, are compared with the costs arising in a Viterbi-based manoeuvre estimator due to Averbuch, et al. (1991). It is shown that the two criteria differ only in the weighting matrix of the quadratic part of the cost function. Simulations are provided to demonstrate the performance of both the batch and recursive estimators compared with Averbuch's method and the interacting multiple model filter View full abstract»

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  • Performance evaluation of track fusion with information matrix filter

    Publication Year: 2002 , Page(s): 455 - 466
    Cited by:  Papers (56)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (956 KB) |  | HTML iconHTML  

    In a multisensor environment, each sensor detects multiple targets and creates corresponding tracks. Fusion of tracks from these, possibly dissimilar, sensors yields more accurate kinematic and attribute information regarding the target. Two methodologies have been employed for such purpose, which are: measurement fusion and state vector fusion. It is well known that the measurement fusion approach is optimal but computationally inefficient and the state vector fusion algorithms are more efficient but suboptimal, in general. This is so because the state vector estimates to be fused obtained from two sensors, are not conditionally independent in general due to the common process noise from the target being tracked. It is to be noted that there are three approaches to state vector fusion, which are: weighted covariance, information matrix, and pseudomeasurement. This research is restricted solely to performance evaluation of the information matrix form of state vector fusion. Closed-form analytical solution of steady state fused covariance has been derived as a measure of performance using this approach. Note that the results are derived under the assumptions that the two sensors are synchronized and no misassociation or merged measurement is considered in the study. Results are compared with those using Monte Carlo simulation, which was used in the past to predict fusion system performance by various authors. These results provide additional insight into the mechanism of track fusion and greatly simplify evaluation of fusion performance. In addition, availability of such a solution facilitates the trade-off studies for designing fusion systems under various operating conditions View full abstract»

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  • The evolution of digital signal processing for airborne radar

    Publication Year: 2002 , Page(s): 723 - 733
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1623 KB) |  | HTML iconHTML  

    The author presents his personal experience in the development and feasibility demonstration of signal processing for military radar systems View full abstract»

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  • Data fusion of multiradar system by using genetic algorithm

    Publication Year: 2002 , Page(s): 601 - 612
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (957 KB) |  | HTML iconHTML  

    Detection system with distributed sensors and data fusion. are increasingly being used by surveillance systems. There has been a great deal of theoretical study on decentralized detection networks composed of identical or non-identical sensors. To solve the resulting nonlinear system, exhaustive search and some crude approximations are adopted. However, those methods often cause either the system to be insensitive to some parameters or the suboptimal results. In this paper, a novel flexible genetic algorithm is investigated to obtain the optimal results on constant false alarm rate data fusion. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. The simulation results show that adopting the proposed approach, one can achieve better performances than the reported methods and results View full abstract»

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  • Low altitude target model for radar simulation

    Publication Year: 2002 , Page(s): 668 - 675
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (753 KB) |  | HTML iconHTML  

    A simulation model of antenna array signals from a low altitude target is considered. Explicit expressions for statistical and spectral characteristics of the scattered signals are obtained in the Kirchhoff approximation. The model permits to evaluate the efficiency of different techniques of low altitude target tracking. It benefits the comprehension of the influence of multipath propagation on tracking radars View full abstract»

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  • 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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  • Tracking considerations in selection of radar waveform for range and range-rate measurements

    Publication Year: 2002 , Page(s): 467 - 487
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1623 KB) |  | HTML iconHTML  

    The conventional approach for tracking system design is to treat the detection and tracking subsystems as completely independent units. However, the two subsystems can be designed jointly to improve system (tracking) performance. It is known that different radar signal waveforms result in very different resolution cell shapes (for example, a rectangle versus an eccentric parallelogram) in the range/range-rate space, and that there are corresponding differences in overall tracking performance. We develop a framework for the analysis of this performance. An imperfect detection process, false alarms, target dynamics, and the matched filter sampling grid are all accounted for, using the Markov chain approach of Li and Bar-Shalom. The role of the grid is stressed, and it is seen that the measurement-extraction process from contiguous radar "hits" is very important. A number of conclusions are given, perhaps the most interesting of which is the corroboration in the new measurement space of Fitzgerald's result for delay-only (i.e., range) measurements, that a linear FM upsweep offers very good tracking performance View full abstract»

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  • Pade approximations to matched-filter amplitude probability functions: Rayleigh mixtures and multiple observations

    Publication Year: 2002 , Page(s): 621 - 632
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (926 KB) |  | HTML iconHTML  

    Techniques are presented for deriving approximations to the statistical functions that characterize linear sums of matched-filter outputs. They are derived using two techniques: (1) Pade approximations to the multidimensional characteristic function (CF), and (2) discrete Rayleigh mixtures based on an exact or approximate form of the Rayleigh parameter probability density function. The Pade-based approximations are used for modeling the "clutter-only" case and computing detection thresholds, whereas the Rayleigh mixtures are best suited for modeling the "target-plus-clutter" case and computing target detection probabilities View full abstract»

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  • Role of processing geometry in SAR raw data focusing

    Publication Year: 2002 , Page(s): 441 - 454
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1376 KB) |  | HTML iconHTML  

    Synthetic aperture radar (SAR) systems require that a focusing operation be performed on the received backscattered echoes (raw data) to generate high-resolution microwave images. Either due to platform attitude instabilities, or to Earth rotation effects, the SAR raw data may be acquired in "squinted" geometries, i.e., with the radar beam directed with an offset angle (squint angle) from the broadside direction. This research investigates the impact of the focusing operation carried out on squinted raw data acquisitions performed by SAR sensors operating in the stripmap mode. To this end the 2D frequency SAR processing approach is generalized with respect to conical, i.e., nonorthogonal, reference systems. This allows analysis of the geometric, spectral, and phase aberrations introduced in the images by the chosen processing geometry with respect to the acquisition, and identification of the focusing procedure that minimizes these aberrations. The whole theory is validated by experimental results carried out on simulated data. Moreover, the extension of this analysis to the interferometric case where these aberrations may have a significant role is also investigated View full abstract»

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  • Layernet: a self-organizing protocol for small ad hoc networks

    Publication Year: 2002 , Page(s): 378 - 387
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1025 KB) |  | HTML iconHTML  

    A self-organizing protocol is proposed for small ad hoc networks. Among this protocol's original features is the initial creation of an asynchronous sparse tree topology followed by a transition to a more fully connected network and synchronous scheduling. An efficient address bundling technique and unique reliability simulation results for this protocol are also presented View full abstract»

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  • Space Interferometry Mission spacecraft pointing error budgets

    Publication Year: 2002 , Page(s): 502 - 514
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1250 KB) |  | HTML iconHTML  

    Preliminary error budgets for the pointing knowledge, control, and stability of the Space Interferometry Mission (SIM) spacecraft are constructed using the specifications of commercial off-the-shelf attitude determination sensors, attitude control actuators, and other spacecraft capabilities that have been demonstrated in past missions. Results obtained indicate that we can meet all the presently known spacecraft pointing requirements. A large number of derived requirements are generated from this study. Examples are specifications on attitude determination sensors, attitude control actuators, minimum settling time after a rest-to-rest spacecraft slew. Preliminary error budgets constructed in this study must be updated to reflect the changing spacecraft design and requirements View full abstract»

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  • Local and nonlocal robustness measures with application to distributed sensor systems

    Publication Year: 2002 , Page(s): 675 - 681
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (653 KB)  

    We investigate the robustness of distributed sensor systems by considering the case where the system consists of N sensors which make independent decisions, whereupon the fusion center implements a Neyman-Pearson (NP) test. Applying geometric techniques, we obtain robustness measures which allow the computation of the approximate change in overall false alarm probability and overall detection probability as the corresponding sensor probabilities are perturbed from these nominal values. We consider both the situation where all sensors experience perturbation and the situation where only one sensor is perturbed. Our analysis is based on local (linearized) methods which are valid for only small perturbations, but we also extend these methods to the more practical nonlocal case where larger perturbations are admitted View full abstract»

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  • Adaptive early-detection ML-PDA estimator for LO targets with EO sensors

    Publication Year: 2002 , Page(s): 694 - 707
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1225 KB) |  | HTML iconHTML  

    The batch maximum likelihood estimator, combined with the probabilistic data association algorithm (ML-PDA), has. been shown to be effective in acquiring low observable (LO)-low signal-to-noise ratio (SNR)-nonmaneuvering targets in the presence of heavy clutter. The use of signal strength or amplitude information (AI) in the ML-PDA estimator facilitates the acquisition of weak targets. We present an adaptive algorithm, which uses the ML-PDA estimator with AI in a sliding-window fashion, to detect possibly maneuvering targets in heavy clutter using electro-optical (EO) sensors. The initial time and the length of the sliding window are adjusted adaptively according to the information content of the received measurements. A track validation scheme via hypothesis testing is developed to confirm the estimated track, that is, the presence of a target, in each window. The sliding-window ML-PDA approach, together with track validation, enables early track detection by rejecting noninformative scans, target reacquisition in case of temporary target disappearance, and the handling of targets with velocities evolving over time. We demonstrate the operation of the adaptive sliding-window ML-PDA estimator on a real scenario for tracking a fast-moving F1 Mirage fighter jet using an imaging sensor. The proposed algorithm is shown to detect the target, which is hidden in as many as 600 false alarms per scan, 10 frames earlier than the multiple hypothesis tracking algorithm. This ability to successfully process large amounts of data, with near real-time performance, under time-varying low SNR conditions makes the proposed estimator superior to other existing approaches View full abstract»

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  • VLSI architecture for SAR data compression

    Publication Year: 2002 , Page(s): 427 - 440
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1117 KB) |  | HTML iconHTML  

    As a step towards a real-time signal aperture radar (SAR) correlator, custom very large scale integration (VLSI) architectures are developed. Considering the extremely short word length of the data, we derive three architectures with massive parallelism in bit space. Unlike frequency methods, no. degradation is introduced during convolution. Optimized for time and space, they are highly suited to VLSI implementation, and a small architecture with 80 taps operating at 10 MHz has been built using an FPGA View full abstract»

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  • CFAR detection of distributed targets in non-Gaussian disturbance

    Publication Year: 2002 , Page(s): 612 - 621
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (838 KB) |  | HTML iconHTML  

    The subject of detection of spatially distributed targets in non-Gaussian noise with unknown statistics is addressed. At the design stage, in order to cope with the a priori uncertainty, we model noise returns as Gaussian vectors with the same structure of the covariance matrix, but possibly different power levels (heterogeneous environment). We also assume that a set of secondary data, free of signal components, is available to estimate the correlation properties of the disturbance The proposed detector assumes no a priori knowledge about the spatial distribution of the target scatterers and ensures the constant false alarm rate (CFAR) property with respect to both the structure of the covariance matrix and the power levels. Finally, the performance assessment, conducted modeling the disturbance as a spherically invariant random process (SIRP), confirms its validity to operate in real radar scenarios View full abstract»

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  • Generalized switched inductor model (GSIM): accounting for conduction losses

    Publication Year: 2002 , Page(s): 681 - 687
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (682 KB) |  | HTML iconHTML  

    The method of average modeling and simulation of pulsewidth modulation (PWM) converters is extended to include conduction losses. The method covers losses due to the inductor's resistance and due to the voltage drops across the switch and the diode. The method is demonstrated by considering an average model that is applicable to both current conduction mode (CCM) and discontinuous conduction mode (DCM) operations, and the switching from one to the other is automatic. The large-signal model is SPICE compatible and as such can be used to run DC (steady state), TRAN (large signal, time domain) and AC (small signal, frequency domain) analyses 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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Meet Our Editors

Editor-in-Chief
Lance Kaplan
Army Research Laboratory