新型机载双通道SAR-GMTI实时算法

提出了一种用于机载双通道SAR的GMTI新算法,将自适应插值算法与多普勒频域DPCA相结合,先分析了新算法的原理,然后以一个距离误差系数不为正整数,并且有加速度存在的载机模型进行仿真.给出了使用新算法后的仿真结果,证明了算法的合理性和可靠性.     

Airborne/spacebased radar STAP using a structured covariance matrix

It is shown that partial information about the airborne/spacebased (A/S) clutter covariance matrix (CCM) can be used effectively to significantly enhance the convergence performance of a block-processed space/time adaptive processor (STAP) in a clutter and jamming environment. The partial knowledge of the CCM is based upon the simplified general clutter model (GCM) which has been developed by the airborne radar community. A priori knowledge of parameters which should be readily measurable (but not necessarily accurate) by the radar platform associated with this model is assumed. The GCM generates an assumed CCM. The assumed CCM along with exact knowledge of the thermal noise covariance matrix is used to form a maximum likelihood estimate (MLE) of the unknown interference covariance matrix which is used by the STAP. The new algorithm that employs the a priori clutter and thermal noise covariance information is evaluated using two clutter models: 1) a mismatched GCM, and 2) the high-fidelity Research Laboratory STAP clutter model. For both clutter models, the new algorithm performed significantly better (i.e., converged faster) than the sample matrix inversion (SMI) and fast maximum likelihood (FML) STAP algorithms, the latter of which uses only information about the thermal noise covariance matrix.     

Recursive estimation of radar biases using electronic charts

This work describes the application of the extended Kalman filter (EKF) to the estimation of range and bearing biases in marine radars by performing a map-matching between the data from hydrographic charts and the radar images. By defining at least two corresponding points from the radar image and the electronic charts, the technique provides a rapid and accurate calibration in range and bearing, giving also estimates for the speed, heading, latitude, and longitude of the ship. The method is tested with simulated data to check convergence and later with real data obtained from a navigation console installed on a patrol boat The technique does not require GPS nor speed information from the ship log unit, however it is shown that their inclusion can improve the estimation.     

Multimode adaptive signal processing: a new approach to GMTI radar

We show how a single reflector antenna with a multimode feed horn can be used in a ground moving target indication (GMTI) radar. In particular, we demonstrate the simultaneous detection and estimation of angular location of a ground moving target via adaptive cancellation of ground clutter     

Robust altitude estimation for over-the-horizon radar using a state-space multipath fading model

In previous work, a matched-field estimate of aircraft altitude from multiple over-the-horizon (OTH) radar dwells was presented. This approach exploits the altitude dependence of direct and surface reflected returns off the aircraft and the relative phase changes of these micro-multipath arrivals across radar dwells. Since this previous approach assumed high dwell-to-dwell predictability, it has been found to be sensitive to mismatch between modeled versus observed micro-multipath phase and amplitude changes from dwell-to-dwell. A generalized matched-field altitude estimate is presented here based on a state-space model that accounts for random ionospheric and target-motion effects that degrade the dwell-to-dwell predictability of target returns. The new formulation results in an efficient, robust recursive maximum likelihood (ML) estimation of aircraft altitude. Simulations suggest that the proposed technique can achieve accuracy within 5,000 ft of the true aircraft altitude, even with relatively high levels of uncertainty in modeling of dwell-to-dwell changes in the target return. A real data result is also presented to illustrate the technique.     

Airborne radar: its beginnings in World War II

Although not realized at the time, the defeat of the German Air Force in the summer of 1940 was one of the crucial battles of World War II. The narrow margin of victory can be ascribed to Britain's air-warning radar, Chain Home (CH), consisting of the 15-meter CH and the 1.5-meter CHL. The skillful use of this equipment by the Royal Air Force made daylight bombing unsustainable; the Luftwaffe then turned to night attacks, generally called "The Blitz." These were not effective in destroying military and industrial targets and depended on the hope of reducing the population's will to fight. Chain Home was of little use except to observe the attackers arrival, as it had almost no ability to follow the attackers as they proceeded inland. This eventuality was reckoned with before the outbreak of hostilities and had called for radars mounted in night fighters capable of guiding the pilot close enough to the target for him to open fire visually. The electronic techniques used at 1.5-meters were adapted to planes capable of carrying the radar and its operator. But there were three important design constraints: 1) the antennas had to be restricted to sizes that were practical for installation on aircraft, which for meter waves gave them low gain and large side lobes; 2) the set's maximum range was limited by the fighter's altitude as a result of the huge ground returns from the side lobes. British antiaircraft artillery, the stepchild of their arms, was too ineffective to drive the bombers to extreme altitudes; and 3) a minimum range had to be held until the flier could see his target, which strained the pulse techniques of the time.     

Processing throughput estimation for radar intercept receivers

Analytical expressions for the computational requirements of broad classes of radar pulse deinterleaving algorithms are developed. The analysis applies to block collection systems and is principally intended for systems with insufficient monopulse resolution to uniquely sort emitters on monopulse parameters alone. The analysis begins with triplet sequence search approaches and is confirmed by simulation. It is also shown that this approach generalizes to more complex deinterleaving schemes, including M-tuple search and time of arrival (TOA) difference histogramming. All cases exhibit the same basic functional form of quadratic dependence on the number of emitters, linear dependence on the collection time, and complex dependence on the pulse deletion (or dropping) probability     

Exact multisensor dynamic bias estimation with local tracks

An exact solution is provided for the multiple sensor bias estimation problem based on local tracks. It is shown that the sensor bias estimates can be obtained dynamically using the outputs of the local (biased) state estimators. This is accomplished by manipulating the local state estimates such that they yield pseudomeasurements of the sensor biases with additive noises that are zero-mean, white, and with easily calculated covariances. These results allow evaluation of the Cramer-Rao lower bound (CRLB) on the covariance of the sensor bias estimates, i.e., a quantification of the available information about the sensor biases in any scenario. Monte Carlo simulations show that this method has significant improvement in performance with reduced rms errors of 70% compared with commonly used decoupled Kalman filter. Furthermore, the new method is shown to be statistically efficient, i.e., it meets the CRLB. The extension of the new technique for dynamically varying sensor biases is also presented.     

Noise covariances estimation for systems with bias states

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     

Attitude determination with UD implementation of decoupled bias estimation

The application of the UD implementation decoupled bias estimation to attitude determination is analyzed here. The advantage of decoupled bias estimation in general is the reduction in the dimensions of the filter and the subsequent reduction in the amount of processing. The purpose of the UD implementation is to mitigate the effects of round-off errors. A unique advantage of the application of decoupled bias estimation to attitude determination is that the bias processing can easily be turned off whenever a reconfiguration to a bias-free estimator mode is necessary. A comparison of the attitude error of the UD decoupled Kalman filter attitude uncertainty is given with respect to the coupled Kalman filter attitude uncertainty during the time periods when the bias processing is turned off. A detailed discussion of the UD implementation is given.     

Angle estimation for two unresolved targets with monopulse radar

Most present-day radar systems use monopulse techniques to extract angular measurements of sunbeam accuracy. The familiar "monopulse ratio" is a very effective means to derive the angle of a single target within a radar beam. For the simultaneous estimation of the angles of two closely-spaced targets, a modification on the monopulse ratio was derived in (Blair and Pearce, 2001), while (Sinha et al., 2002) presented a maximum likelihood (ML) technique via numerical search. In this paper it is shown that the ML solution can in fact be found explicitly, and the numerical search of ((Sinha et al., 2002) is unnecessary. However, the ML solution requires the signal to noise ratio (SNR) for each target to be known, and hence we generalize it so it requires only the relative SNR. Several versions of expectation maximization (EM) joint angle estimators are also derived, these differing in the degree to which prior information on SNR and on beam pattern are assumed. The performances of the different direction-of-arrival (DOA) estimators for unresolved targets are studied via Monte Carlo, and it is found that most have similar performance: this is remarkable since the use of prior information (SNR, relative SNR, beam pattern) varies widely between them. There is, however, considerable performance variability as a function of the two targets' off-boresight angles. A simple combined technique that fuses the results from different approaches is thus proposed, and it performs well uniformly.     

Airborne radar. [A century of powered flight: 1903-2003]

Radar is one of the major AESS disciplines and has been a major focus of papers and articles. This issue focuses on aviation and emphasizes the evolution of airborne radar systems through WW II.     

MIMO雷达中一种降维MUSIC的相干角度估计算法

研究单快拍下双基地多输入多输出（Multiple—InputMultiple-Output,MIMO）雷达中相干信源的离开角（Directionofdeparture,DOD）与到达角（directionofarrival,DOA）联合估计问题。利用单快拍下双基地MIMO雷达的接收信号构造一组Toeplitz矩阵,利用这组ToepIitz矩阵重构一个信号矩阵,提出一种基于降维多重信号分类（ReducedDimensionMultipleSignalClassification,RD-MUSIC）的DOD与DOA联合估计算法。提出的算法能够有效估计相干信源以及非相干信源的角度,实现角度的自动配对,并且角度估计性能远优于FBSS—ESPRIT算法以及ESPRIT-like算法。仿真结果验证了算法的有效性。     

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation (CPPM) and linear frequency modulation (LFM), which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval (PRI) of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform (CHT) algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio (SNR) is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.     

Enhanced target detection using stereoscopic imaging radar

An earlier correspondence reported experiments which suggested that the visibility of a target in clutter could be improved through stereoscopic viewing of high resolution radar images. Here we provide a more thorough discussion on the application of stereo for improving radar detection and recognition. Experiments are reported which confirm and extend the earlier reported results. An example of the use of stereo in a practical system is provided which demonstrates the potential for acquisition of high quality radar stereograms     

Distributed weather radar using X-band active arrays

Dense networks of short-range radars capable of mapping storms and detecting atmospheric and airborne hazards are described. Comprised of physically small, low-power antennas, these networks defeat the Earth curvature blockage that limits today's long-range radar networks and enable high resolution views that extend from the lower-troposphere to the tops of storms. The networks are comprised of 1-meter antennas that transmit 10's of W peak power and are capable of high-speed electronic beam-steering. A system architecture is described that maximizes the value accrued to users of radar data through utility functions that specify dynamic, optimal allocation of resources in response to the needs of multiple end-users and associated information retrieval algorithms.     

Synthetic-aperture radar processing using fast factorized back-projection

Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude.     

Classification of radar targets using synthetic neural networks

Radar target classification performance of neural networks is evaluated. Time-domain and frequency-domain target features are considered. The sensitivity of the neural network algorithm to changes in network topology and training noise level is examined. The problem of classifying radar targets at unknown aspect angles is considered. The performance of the neural network algorithms is compared with that of decision-theoretic classifiers. Neural networks can be effectively used as radar target classification algorithms with an expected performance within 10 dB (worst case) of the optimum classifier     

An interpolation algorithm to improve range estimation for thelinear frequency modulated radar

Radar with the linear frequency-modulated signal may range the target. Its range resolution is decided by the signal frequency bandwidth. This paper proposes an interpolation algorithm based on fast Fourier transform to improve the accuracy of range estimation without increasing the frequency bandwidth. The algorithm application in practice is described. The simulation result of estimation accuracy is also given     

Applications and frustrations in using ground penetrating radar

In this paper the author concentrates on the narrow portion of the electromagnetic spectrum from a few MHz to a few GHz where geophysicists used ground penetrating radar which is sometimes called georadar, ground probing radar, or subsurface radar. Ground penetrating radar is deployed today from the space shuttle, aircraft, on the surface, in and between boreholes and sometimes from within or between mine shafts. The author discusses these applications and some of the problems involved