Showing papers in "IEEE Transactions on Aerospace and Electronic Systems in 1998"

Interacting multiple model methods in target tracking: a survey

Abstract: 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.

Implementation of the simultaneous perturbation algorithm for stochastic optimization

Abstract: The need for solving multivariate optimization problems is pervasive in engineering and the physical and social sciences. The simultaneous perturbation stochastic approximation (SPSA) algorithm has recently attracted considerable attention for challenging optimization problems where it is difficult or impossible to directly obtain a gradient of the objective function with respect to the parameters being optimized. SPSA is based on an easily implemented and highly efficient gradient approximation that relies on measurements of the objective function, not on measurements of the gradient of the objective function. The gradient approximation is based on only two function measurements (regardless of the dimension of the gradient vector). This contrasts with standard finite-difference approaches, which require a number of function measurements proportional to the dimension of the gradient vector. This paper presents a simple step-by-step guide to implementation of SPSA in generic optimization problems and offers some practical suggestions for choosing certain algorithm coefficients.

Biased PNG law for impact with angular constraint

Abstract: A new homing guidance law is proposed to impact a target with a desired attitude angle. It is a variation of the conventional proportional navigation guidance (PNG) law which includes a supplementary time-varying bias. The proposed guidance law does not require a time-to-go estimation and has a simpler form. Analytic conditions for fulfilling the guidance goal are also provided. Simulation results demonstrate that the proposed guidance law has wider launch envelopes than the previous one and shows a good performance even against a maneuvering target.

Unbiased converted measurements for tracking

Abstract: The exact compensation for the bias in the classical polar-to-Cartesian conversion is shown to be multiplicative and to depend on the statistics of the cosine of the angle measurement errors. An unbiased conversion is presented. A comparison between this unbiased conversion and the previously presented debiased conversion is made. The unbiased spherical-to-Cartesian conversion is also presented and evaluated.

Joint time-frequency transform for radar range-Doppler imaging

Abstract: Conventional radar imaging uses the Fourier transform to retrieve Doppler information. However, due to the complex motion of a target, the Doppler frequency shifts are actually time-varying. By using the Fourier transform, the Doppler spectrum becomes smeared and the image is blurred. Without resorting to sophisticated motion compensation algorithms, the image blurring problem can be resolved with the joint time-frequency transform. High-resolution time-frequency transforms are investigated, and examples of applications to radar imaging of single and multiple targets with complex motion are given.

Detection and diagnosis of sensor and actuator failures using IMM estimator

Abstract: An approach to detection and diagnosis of multiple failures in a dynamic system is proposed. It is based on the interacting multiple-model (IMM) estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural as well as parametric changes. The proposed approach provides an integrated framework for fault detection, diagnosis, and state estimation. It is able to detect and isolate multiple faults substantially more quickly and more reliably than many existing approaches. Its superiority is illustrated in two aircraft examples for single and double faults of both sensors and actuators, in the forms of "total", "partial", and simultaneous failures. Both deterministic and random fault scenarios are designed and used for testing and comparing the performance fairly. Some new performance indices are presented. The robustness of the proposed approach to the design of model transition probabilities, fault modeling errors, and the uncertainties of noise statistics are also evaluated.

ISAR motion compensation via adaptive joint time-frequency technique

Abstract: A novel approach for inverse synthetic aperture radar (ISAR) imaging is presented for both target translational motion and rotational motion nonuniformity compensation. The basic idea is to perform Doppler tracking to individual scatterers via an adaptive joint time-frequency (AJTF) projection technique. After maximizing the projection of the phase function to a set of basis functions in time-frequency plane, the Doppler frequency drift of the strongest scatterer in the range bin is automatically tracked out and the multiple prominent point processing (PPP) scheme is implemented to eliminate both the translational motion error and rotational motion nonuniformity. Further the azimuth spacing can be estimated, which permits polar reformatting of the original collected data.

Benchmark for radar allocation and tracking in ECM

Abstract: A benchmark problem for tracking maneuvering targets is presented. The benchmark problem involves beam pointing control of a phased array (i.e., agile beam) radar against highly maneuvering targets in the presence of false alarms (FAs) and electronic counter measurements (ECM). The testbed simulation described includes the effects of target amplitude fluctuations, beamshape, missed detections, FAs, finite resolution, target maneuvers, and track loss. Multiple waveforms are included in the benchmark so that the radar energy can be coordinated with the tracking algorithm. The ECM includes a standoff jammer (SOJ) broadcasting wideband noise and targets attempting range gate pull off (RGPO). The limits on the position and maneuverability of the targets are given along with descriptions of six target trajectories. The "best" tracking algorithm is the one that minimizes a weighted average of the radar energy and radar time, while satisfying a constraint of 4% on the maximum number of lost tracks, The radar model, the ECM techniques, the target scenarios, and performance criteria for the benchmark are presented.

IMMPDAF for radar management and tracking benchmark with ECM

Abstract: A framework is presented for controlling a phased array radar for tracking highly maneuvering targets in the presence of false alarms (FAs) and electronic countermeasures (ECMs). Algorithms are presented for track formation and maintenance; adaptive selection of target revisit interval, waveform and detection threshold; and neutralizing techniques for ECM, namely, against a standoff jammer (SOJ) and range gate pull off (RGPO). The interacting multiple model (IMM) estimator in combination with the probabilistic data association (PDA) technique is used for tracking. A constant false alarm rate (CFAR) approach is used to adaptively select the detection threshold and radar waveform, countering the effect of jammer-induced false measurements. The revisit interval is selected adaptively, based on the predicted angular innovation standard deviations. This tracker/radar-resource-allocator provides a complete solution to the benchmark problem for target tracking and radar control. Simulation results show an average sampling interval of about 2.5 s while maintaining a track loss less than the maximum allowed 4%.

Optimal observer maneuver for bearings-only tracking

Abstract: In bearings-only tracking, observer maneuver is critical to ensure observability and to obtain an accurate target localization. Here, optimal control theory is applied to the determination of the course of a constant speed observer that minimizes an accuracy criterion deduced from the Fisher information matrix (FIM). Necessary conditions for optimal maneuver (Euler equations) are established and resolved, partly by analytical means and partly by an iterative numerical procedure. Examples of optimal observer maneuvers are presented and discussed.

Fault diagnostics and fault tolerant control

Abstract: A novel simultaneous fault detection and diagnostics (FDD) and fault tolerant control (FTC) strategy for nonlinear stochastic systems in closed loops based on a continuous stirred tank reactor (CSTR) is presented. The purpose of control is to track the reactant concentration setpoint. Instead of output feedback we propose here to use proportional-integral-derivative (PID) state feedback, which is shown essential to achieve FTC against sensor faults. A new concept of "equivalent bias" is proposed to model the sensor faults. Both the states and the equivalent bias are on-line estimated by a pseudo separate-bias estimation algorithm. The estimated equivalent bias is then evaluated via a modified Bayes' classification based algorithm to detect and diagnose the sensor faults. Many kinds of sensor faults are tested by Monte Carlo simulations, which demonstrate that the proposed strategy has definite fault tolerant ability against sensor faults, moreover the sensor faults can be on-line detected, isolated, and estimated simultaneously.

Unified approach to developing single-stage power converters

Abstract: A unified approach to developing single-stage power converters which can fulfil multiple functions is presented. Four synchronous switches corresponding to the four common node types of two active switches are introduced. The approach is then to replace the active switches in multistage converters (in cascade or cascode connection) with one or several of the synchronous switches and their degenerated versions to form a single-stage converter. Illustrations of using these switches to develop single-stage converters are presented. These are started with the development of the well-known single-stage switch-mode converters (SMCs), buck-boost, Cuk, sepic, and Zeta (also named dual sepic), from the basic converters, buck and boost. Then, synthesis and applications of other single-stage converters are addressed. Due to increased component stresses, the developed single-stage converters are primarily suitable for applications with moderate power levels.

Error analysis of analytic coarse alignment methods

Abstract: Two analytic coarse alignment methods and the associated error analyses are provided for strapdown inertial navigation systems. Although both methods are derived from the same measurements of the local gravity vector and Earth rate, their error formulations are not completely identical. By properly selecting the basis to compute a best estimate of transformation matrix, the drift misalignment angles of analytic alignment can be made to be equivalent to those which can be found by physical gyrocompassing.

A new fourth-order processing algorithm for spaceborne SAR

Abstract: A new fourth-order signal aperture radar (SAR) processing algorithm has been developed for a general satellite-Earth relative motion. The two-dimensional exact transfer function (ETF) is calculated and range-variant phase corrections have been calculated in order to process many azimuth lines per block. The ETF together with the phase corrections has been called the fourth-order EETF (extended ETF). It is also shown that a fourth-order EETF is necessary to process high quality images from spaceborne SAR with long integration times with spatial resolution around 1 m. The algorithm is fast and is anticipated to have good phase preservation properties.

Maximum likelihood track-before-detect with fluctuating target amplitude

Abstract: An important problem in target tracking is the detection and tracking of targets in very low signal-to-noise ratio (SNR) environments. In the past, several approaches have been used, including maximum likelihood. The major novelty of this work is the incorporation of a model for fluctuating target amplitude into the maximum likelihood approach for tracking of constant velocity targets. Coupled with a realistic sensor model, this allows the exploitation of signal correlation between resolution cells in the same frame, and also from one frame to the next. The fluctuating amplitude model is a first order model to reflect the inter-frame correlation. The amplitude estimates are obtained using a Kalman filter, from which the likelihood function is derived. A numerical maximization technique avoids problems previously encountered in "velocity filtering" approaches due to mismatch between assumed and actual target velocity, at the cost of additional computation. The Cramer-Rao lower bound (CRLB) is derived for a constant, known amplitude case. Estimation errors are close to this CRLB even when the amplitude is unknown. Results show track detection performance for unknown signal amplitude is nearly the same as that obtained when the correct signal model is used.

Adaptive detection schemes in compound-Gaussian clutter

Abstract: Radar detection of coherent pulse trains embedded in compound-Gaussian disturbance with partially known statistics is discussed. We first give a thorough derivation of two recently proposed adaptive detection structures. Next, we derive a different detection scheme exploiting the assumption that the clutter is wide-sense stationary. Resorting to the theory of circulant matrices, in fact, we demonstrate that the estimation of the structure of the clutter covariance matrix can be reduced to the estimation of its eigenvalues, which in turn can be (efficiently) done via fast Fourier transform codes. After a thorough performance assessment, mostly carried on via computer simulations, the results show that the newly proposed detector achieves better performance than the two previously introduced adaptive detectors. Moreover, a sensitivity analysis shows that, even though this detector does not strictly guarantee the constant false alarm rate property with respect to the clutter covariance matrix, it is robust, in the sense that its performance is only slightly affected by variations in the clutter temporal correlation.

A multipath data association tracker for over-the-horizon radar

Abstract: A new algorithm, multipath probabilistic data association (MPDA), for initiation and tracking in over-the-horizon radar (OTHR) is described. MPDA is capable of exploiting multipath target signatures arising from discrete propagation modes that are resolvable by the radar. Nonlinear measurement models exhibiting multipath target signatures in azimuth, slant range, and Doppler are used. Tracking is performed in ground coordinates and therefore depends on the provision of estimates of virtual ionospheric heights to achieve coordinate registration. Although the propagation mode characteristics are assumed to be known, their correspondence with the detections is not required to be known. A target existence model is included for automatic track maintenance. Numerical simulations for four resolvable propagation modes are presented that demonstrate the ability of the technique to initiate and maintain track at probabilities of detection of 0.4 per mode in clutter densities for which conventional probabilistic data association (PDA) has a high probability of track loss, and suffers from track bias. A nearest neighbor version of MPDA is also presented.

Detection of interference/jamming and spoofing in a DGPS-aided inertial system

Abstract: Previous research at the Air Force Institute of Technology (AFIT) has resulted in the design of a differential Global Positioning System (DGPS) aided INS-based (inertial navigation system) precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to both intentional and nonintentional interference/jamming and spoofing must be addressed before DGPS may be safely used as a major component of such a critical navigational device. This research applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of each hypothesis being correct, to form a probability-weighted average state estimate as an output. For interference/jamming degradation represented as increased measurement noise variance, simulation results show that, because of the good failure detection and isolation (FDI) performance using MMAE, the blended navigation performance is essentially that of a single extended Kalman filter (EKF) artificially informed of the actual interference noise variance. However, a standard MMAE is completely unable to detect spoofing failures (modeled as a bias or ramp offset signal directly added to the measurement). This work describes a moving-bank pseudoresidual MMAE (PRMMAE) to detect and identify such spoofing. Using the PRMMAE algorithm, spoofing is very effectively detected and isolated; the resulting navigation performance is equivalent to that of an EKF operating in an environment without spoofing.

Charge equalization for an electric vehicle battery system

Abstract: Charge equalization for series connected battery strings has important ramifications on battery life. It enhances the uniformity of the battery cells and hence improves the life of the battery as a whole. A new charge equalization technique for a series string of battery cells has been recently proposed by the authors. The basic technique utilizes a simple isolated dc-to-dc converter with a capacitive output filter along with a multiwinding transformer. The possibility of integrating the trickle charge function with the charge equalization function is potentially very attractive, as it can lead to an efficient and low cost implementation.

Adaptive SNR-based carrier phase multipath mitigation technique

Abstract: An improved technique that mitigates specular multipath in Global Positioning System (GPS) differential carrier phase measurements is described. It adaptively estimates the spectral parameters (frequency, amplitude, phase offset) of multipath in the associated signal-to-noise ratio (SNR), and then constructs a profile of the multipath error in the carrier phase. A multipath correction is subsequently made by subtracting the profile from the actual phase measurement data. The technique is demonstrated on ground based experimental data, as well as flight data from the atmospheric research satellite CRISTA-SPAS. Ground experiments were conducted on static platforms in severe multipath environments. Multipath was deliberately introduced by either strategic placement of reflectors or electronic injection. This allowed for some control over the strength and frequency of the multipath. Averaging the results from 43 ground and 18 flight data sets, the differential carrier phase multipath was reduced by 47%. The complete results for both ground and flight tests are presented and are accompanied by discussions of individual cases.

Range, radial velocity, and acceleration MLE using radar LFM pulse train

Abstract: An efficient implementation of the maximum likelihood estimator (MLE) is presented for the estimation of target range, radial velocity, and acceleration when the radar waveform consists of a wideband linear frequency modulated (LFM) pulse train. Analytic properties of the associated wideband ambiguity function are derived; in particular the ambiguity function, with acceleration set to zero, is derived in closed form. Convexity and symmetry properties of the ambiguity function over range, velocity, and acceleration are presented; these are useful for determining region and speed of convergence for recursive algorithms used to compute the MLE. In addition, the Cramer-Rao bound (CRB) is computed in closed form which shows that the velocity bound is decoupled from the corresponding bounds in range and acceleration. A fast MLE is then proposed which uses the Hough transform (HT) to initialize the MLE algorithm. Monte Carlo simulations show that the MLE attains the CRB for low to moderate signal-to-noise depending on the a priori estimates of range, velocity, and acceleration.

VSAR: a high resolution radar system for ocean imaging

Abstract: The velocity synthetic aperture radar (VSAR) is a conceptual synthetic aperture radar (SAR)-based sensor system for high resolution ocean imaging. The VSAR utilizes data collected by a multielement SAR system, to extract information not only about the radar reflectivity of the observed area, but also about the radial velocity of the scatterers in each pixel. This is accomplished by making use of the phase information contained in multiple SAR images, and not just the magnitude information as in conventional SAR. Using this velocity information, the VSAR attempts to compensate for the velocity distortion inherent in conventional SAR and to reconstruct the ocean reflectivity. We present the basic theory of the VSAR system and its performance. We also provide an analysis of the VSAR imaging mechanism for a statistical model of the radar returns, designed to capture the effects of speckle and of resolution degradation due to the decorrelation of the radar returns.

Novel sliding mode controller for synchronous motor drive

Abstract: A novel sliding mode controller with an integral-operation switching surface is proposed. Furthermore, an adaptive sliding mode controller is investigated, in which a simple adaptive algorithm is utilized to estimate the bound of uncertainties. The position control for a permanent magnet (PM) synchronous servo motor drive using the proposed control strategies is illustrated. The theoretical analysis and the theorems for the proposed sliding mode controllers are described in detail. Simulation and experimental results show that the proposed controllers provide high-performance dynamic characteristics and are robust with regard to plant parameter variations and external load disturbance.

Unresolved Rayleigh target detection using monopulse measurements

Abstract: When the returns from two or more targets interfere (i.e., the signals are not resolved in the frequency or time domains) in a monopulse radar system, the direction-of-arrival (DOA) estimate indicated by the monopulse ratio can wander far beyond the angular separation of the targets. Generalized maximum likelihood (GML) detection of the presence of unresolved Rayleigh targets is developed with probability density functions (pdfs) conditioned on the measured amplitude of the target echoes. The Neyman-Pearson detection algorithm uses both the in-phase and quadrature portions of the monopulse ratio and requires no a priori knowledge of the signal-to-noise ratio (SNR) or DOA of either target. Receiver operating characteristic (ROC) curves are given along with simulation results that illustrate the performance and application of the algorithm.

Decentralized detection over multiple-access channels

Abstract: We study the decentralized detection problem in a general framework where arbitrary number of quantization levels at the local sensors are allowed, and transmission from the sensors to the fusion center is subject to both noise and interchannel interference. We treat both Bayesian and Neyman-Pearson approaches to the problem, and develop an iterative descent algorithm to design the optimal quantizers and fusion rule. Some numerical examples for both approaches are also presented.

A hardware-efficient, multirate, digital channelized receiver architecture

Abstract: An approach is presented to realizing a digital channelized receiver for signal intercept applications that provides a hardware efficient implementation of a uniform filter bank in which the number of filters K is greater than the decimation factor M. The proposed architecture allows simple channel arbitration logic to be used and provides reliable instantaneous frequency measurements, even in adjacent channel crossover regions. In the proposed implementation of the filter bank, K is related to M by K=FM where F is an integer. It is shown that the optimum selection of F allows the instantaneous frequency measurement to be made in the channel crossover region and the arbitration function to be based solely on the instantaneous frequency measurement. The development of a filter bank structure which combines the flexibility of the short-time Fourier transform (STFT) with the implementation efficiency of the polyphase filter bank decomposition, meeting these requirements and leading to a hardware-efficient implementation, is presented.

Sliding mode control of the space nuclear reactor system

Abstract: The automatic control system (ACS) of the space nuclear reactor power system TOPAZ II that generates electricity from nuclear heat using in-core thermionic converters is considered. Sliding mode control technique is applied to the reactor system controller design in order to improve robustness and accuracy of tracking of a thermal power reference profile in a start-up regime and a payload current reference profile in an operation regime. Extensive simulations of the TOPAZ II reactor system with the designed sliding mode controller showed an improvement of the reactor system performance.

Detection-tracking performance with combined waveforms

Abstract: It is commonly understood that in radar or active sonar detection systems constant-frequency (CF) pulses correspond to good Doppler but poor delay resolution capability; and that linearly swept frequency (FM) pulses have the opposite behavior. Many systems are capable of both types of operation, and hence in this paper the fusion of such pulses is examined from a system point of view (i.e., tracking performance) via hybrid conditional averaging (HYCA), a new but increasingly accepted technique for evaluating tracking performance in the presence of missed detections. It is shown that tracking errors are highly dependent on the waveform used, and in many situations tracking performance using a good heterogeneous waveform is improved by an order of magnitude when compared with a scheme using a homogeneous pulse (CF or FM) with the same energy. Between the two types of FM considered (upsweep and downsweep), it is shown that the upsweep is always superior. Also investigated is an alternating-pulse system, which, while suboptimal, appears to offer robust performance.

An efficient algorithm for multisensor track fusion

Abstract: An efficient algorithm for track-to-track fusion by incorporating cross-covariance between tracks created by dissimilar sensors is described. An analytical solution of this problem is complicated if cross-correlation between sensors tracking the same target is taken into account. An explicit solution of the cross-covariance matrix at steady state is derived in terms of an integral. It is shown that solution of this integral involves inversion of a matrix whose elements are functions of parameters of individual trackers. Structure of this matrix is analyzed. An efficient analytical solution for inversion of this matrix is obtained. For fusion of similar sensors, it is shown that this matrix is reduced to the Routh-Hurwitz matrix which arises in the study of steady state stability of linear systems. Numerical results showing the amount of reduction of fused track covariance by taking into account the effects of cross-correlation between candidate tracks for fusion is also presented.

Sequential track extraction

Abstract: Sensors like radar or sonar usually produce data on the basis of a single frame of observation: target detections. The detection performance is described by quantities like detection probability Pd and false alarm density f. A different task of detection is formation of tracks of targets unknown in number from data of multiple consecutive frames of observation. This leads to quantities which are of a higher level of abstraction: extracted tracks. This again is a detection process. Under benign conditions (high Pd, low f and well separated targets) conventional methods of track initiation are recommended to solve a simple task. However, under hard conditions the process of track extraction is known to be difficult. We here concentrate on the case of well separated targets and derive an optimal combinatorial method which can be used under hard operating conditions. The method relates to MHT (multiple hypothesis tracking), uses a sequential likelihood ratio test and derives benefit from processing signal strength information. The performance of the track extraction method is described by parameters such as detection probability and false detection rate on track level, while Pd and f are input parameters which relate to the signal-to-noise interference ratio (SNIR), the clutter density, and the threshold set for target detection. In particular the average test lengths are analyzed parametrically as they are relevant for a user to estimate the time delay for track formation under hard conditions.