Optimum Processing of Unequally Spaced Radar Pulse Trains for Clutter Rejection

A train of radar pulses from one resolution cell can be processed coherently to reject echoes from external clutter and detect targets moving radially with respect to the clutter. Optimum methods of signal processing are defined for systems in which the interpulse spacings are multiply staggered to avoid target blind speeds. Likelihood ratio tests are developed for systems in which the target Doppler frequency is known a priori and for systems employing a bank of filters to cover the target Doppler band. To implement such tests, the N pulses in the train are added with complex weights and the amplitude of the sum compared with a detection threshold. The set of weights which maximizes the average signal-to-clutter ratio is also computed for a single-filter system with unknown target Doppler frequency. When the clutter autocorrelation function is exponential, the clutter covariance matrix can be inverted analytically. This latter result is useful for comparing different interpulse-spacing codes for a particular system application.     

Design and Evaluation of an Adaptive MTI Filter

The design and evaluation of an adaptive moving target indicator (MTI) filter, the adaptive canceler for extended clutter (ACEC) is dealt with, taking into consideration adaptivity to clutter mean Doppler frequency. This consideration is one of the most important operational requirements in adaptive MTI's and permits a relatively simple hardware implementation as compared to more general optimization and adaptivity criteria (briefly described). The ACEC's algorithm compensates in real time for the clutter mean Doppler frequency. Performances have been obtained by digital computer simulation in various operational conditions.     

基于3DT的空时自适应单脉冲参数估计算法

空时自适应处理(STAP)是机载预警雷达抑制杂波和干扰的一项关键技术,而多普勒三通道联合自适应处理(3DT)是适合工程实现的降维(RD)STAP方法。STAP目标检测后还需进一步估计目标的角度参数,因此将自适应单脉冲(AM)技术引入3DT,提出了一种高精度联合估计目标速度与方位空间角的空时自适应单脉冲算法。理论分析与仿真实验结果表明,当目标多普勒频率偏离检测多普勒单元中心频率时,该算法能同时减少目标多普勒跨越损失和空时导引矢量失配损失,进而提高输出信杂噪比(SCNR),改善目标测角精度。     

An Adaptive MTI for Weather Clutter Suppression

A digital realization of an adaptive clutter-locking loop is presented. The purpose of the loop is to estimate the mean Doppler frequency of the clutter. The clutter spectrum is then shifted toward the zero Doppler by this estimate. A fixed moving target indicator (MTI) canceler following the loop suppresses the shifted clutter. Experimental simulations illustrate the feasibility of the loop. Results indicate that the proposed canceler works significantly better than a fixed canceler, while not as well as the 10-pulse moving target detector (MTD) processor. However, the complexity of the MTD is significantly more than the relatively simple adaptive processor presented here.     

MTI Optimization in a Multiple-Clutter Environment

A means of optimizing a moving target indicator (MTI) filter for rejecting several types of clutter, which are generated by different mechanisms such as by rain or the ground, is formulated. lt is found that the optimal performance of such a filter depends on the spectral density functions, average radar cross sections, and the relative mean Doppler frequencies of each type of clutter. lt is shown that the optimal improvement factor of such a filter is bounded by the weighted average (weighted in accordance with the radar cross sections of the clutter types) of the improvement factor for the individual clutter type. lt is also shown that the improvement factor of such a filter is a function of the relative mean Doppler frequency f0 between the clutter types. As f0 increases, the performance of the MTI system degrades. The worst improvement factor occurs when f0 is equal to half of the radar pulse-repetition frequency (PRF).     

Radar/Sonar Signal Design for Bounded Doppler Shifts

In many detection and estimation problems, Doppler frequency shifts are bounded. For clutter or multipath that is uniformly distributed in range and symmetrically distributed in Doppler shift relative to the signal, detectability of a point target or a communication signal is improved by minimizing the weighted volume of the magnitude-squared autoambiguity function. When clutter Doppler shifts are bounded, this volume is in a strip containing the range axis on the range-Doppler plane. For scattering function estimation, e.g., for weather radar, Doppler flow meters, and distributed target classifiers, it is again relevant to minimize ambiguity volume in a strip. Strip volume is minimized by using a pulse train, but such a signal has unacceptably large range sidelobes for most applications. Other waveforms that have relatively small sidelobe level within a strip on the range-Doppler plane, as well as small ambiguity volume in the strip, are obtained. The waveforms are composed of pulse pairs that are phase modulated with Golay complementary codes.     

Properties of Staggered PRF Radar Spectral Components

Expressions for moving target indicator (MTI) improvement factor limitation due to pulse repetition frequency (PRF) staggering and loss of target detectability for various values of Doppler frequency in the passband are presented. It is also shown that the product of variance of stagger periods and clutter variance is an important parameter determining the performance of a staggered PRF MTI radar.     

Reduced-rank STAP for high PRF radar

Due to the range ambiguity of high pulse-repetition frequency (HPRF) radars, echoes from far-range fold over near-range returns. This effect may cause low Doppler targets to compete with near-range strong clutter. Another consequence of the range ambiguity is that the sample support for estimating the array covariance matrix is reduced, leading to degraded performance. It is shown that space-time adaptive processing (STAP) techniques are required to reject the clutter in HPRF radar. Four STAP methods are studied in the context of the HPRF radar problem: low rank approximation sample matrix inversion (SMI), diagonally loaded SMI, eigencanceler, and element-space post-Doppler. These three methods are evaluated in typical HPRF radar scenarios and for various training conditions, including when the target is present in the training data     

无线电引信海面及目标多普勒回波仿真分析

频谱识别技术利用海面及目标回波的多普勒频差来滤除海杂波信号。为准确分析弹目交会时引信回波的多普勒频谱,采用了三维弹目交会模型对弹目不共面时引信回波进行模拟,利用等多普勒线划分海面区域进而计算海面回波多普勒频率,利用目标不同散射点合成的方法推导了目标回波多普勒频率的表达式,并在弹目飞行速率、弹目交会角及目标脱靶量等因素不同时对引信回波多普勒频率进行仿真,通过仿真分析得出了以上因素对引信回波多普勒频率的影响,并验证了频谱识别技术在不同交会条件下的有效性。     

Clutter Performance of Coherent Pulse Trains for Targets with Range Acceleration

The clutter performance of coherent pulse trains is examined when the duration of the pulse train is increased to values for which range acceleration effects must be taken into account. The problem of target detection against a clutter background with differential Doppler is studied in terms of the range acceleration effects on the conventional Doppler response. Specifically considered are the consequences on the sidelobe level and width of the main Doppler lobe. The analysis shows that the sidelobe level remains essentially unchanged when the range acceleration mismatch becomes significant. However, the main Doppler response broadens in proportion to the magnitude of the acceleration mismatch. Thus, an increase of the signal duration for better Doppler resolution is useful only until acceleration effects spread the Doppler spectrum of the clutter and eliminate the differential Doppler between targets and clutter.     

Frequency-Agile Radar Signal Processing

Modern radars may incorporate pulse-to-pulse carrier frequency modulation to increase probability of detection, to reduce Vulnerability to jamming, and to reduce probability of interception. However, if coherent processing is used for clutter rejection, the frequency of N consecutive pulses must be held constant for N-pulse clutter cancellation or Doppler filtering. If M pulses are transmitted during the time the antenna illuminates a target, there are M/N coherently integrated echoes available for noncoherent integration in the computer or the operator's display to further improve the signal-to-noise ratio (SNR). In this paper, analytical and simulation methods are employed to determine the balance between coherent and noncoherent integration that yields the greatest SNR improvement. Attention is focused upon a model using peak selection of fast Fourier transform (FFT) Doppler channels and is compared to a reference model involving only a single Doppler channel. Curves of detectable SNR as a function of M and N are presented for both models.     

Measurements of L-band inland-water surface-clutter Doppler spectra

Although radar surface-clutter reflectivities from terrain are generally much greater than those from water, strong Bragg resonances at low but non-zero Doppler frequencies in backscatter from small inland bodies of water might potentially cause false alarms for moving target indicator (MTI) or other Doppler signal-processing techniques designed for target detection in ground clutter. To provide data for investigating this concern, measurements of L-band radar backscatter were recorded from the surface of a small inland freshwater reservoir in central Massachusetts. These measurements were of unusually high system stability and spectral purity so as to provide up to 80 dB of available spectral dynamic range. Strong Bragg spikes occurred in the clutter Doppler spectra from the reservoir at low (3 to 4 Hz) but non-zero Doppler frequencies. This strong Bragg resonance was persistent in time and space throughout the measurements. Spectral results are presented for all four combinations of linear polarization. Comparison with tree clutter spectral results indicates that, when an occasional water body comes under surveillance at vertical polarization in otherwise generally forested terrain, water clutter spectral density is expected to exceed surrounding-terrain tree clutter spectral densities in the Bragg-offset Doppler vicinity by large amounts     

Low cost Doppler ratio detection radar with interclutter visibility

A low cost concept, called Doppler ratio detection (DRD), for suppressing the clutter residue of Doppler radars is described. The concept provides a simple way to establish a target detect-clutter reject threshold at each range cell, whether a MTI canceler only or a bank of Doppler filters is used. In its simplest form, the target detect/clutter reject threshold is based on the ratio of the magnitudes of Doppler-processed and non-Doppler processed signals. The experiment showed that clutter was rejected, but the amount of added degradation in detection sensitivity was not determined. This degradation will depend on a number of factors, including the number of pulses per beamwidth     

Resolution Performance of Pulse Trains with Large Time-Bandwidth Products

The coherent pulse train has good clutter suppression performance because the energy in its matched-filter response is essentially concentrated within sharp ambiguous spikes. However, this is so only when the Doppler distortions are neglected, so that the Doppler effect is taken as a simple translation of the carrier frequency. This paper analyzes the consequences of Doppler distortions on the resolution performance of pulse trains. It is found that Doppler distortions widen the Doppler ambiguities of the pulse train response, with the widening factor proportional to the order of the Doppler ambiguity. This reduces the interval between Doppler ambiguities, and hence the Doppler width of a clutter space that can be accommodated without severe clutter interference. For an operation in a Doppler-ambiguous mode, it also degrades nominal Doppler resolution performance. A detailed analysis of the effects is presented, and numerical results on the widening of the Doppler ambiguities are obtained.     

Design of MTI Radar on the Basis of Detection Probability

A single (quadrature) channel moving target indicator (MTI) radar system employing a tapped delay line filter is analyzed. The point of view taken is that of optimal clutter rejection in conjunction with subsequent receiver decision operations. The random nature of the spread of target Doppler shifts is taken into account. Based on the above, a procedure is presented by means of which the detection probability can be numerically evaluated for an optimized filter frequency response.     

Radar detection in clutter

Clutter is defined as any unwanted radar return. The presence of clutter in a range/Doppler cell complicates the detection of a target return signal in that cell. In order to quantify the effect of clutter on the probability of detection, we must first specify sets of models suitable for representing the clutter and target. The simplest and most common model for clutter is based on the gamma density. We include two additional models, the NCG and NCGG clutter models for low grazing angles. They are motivated by physical arguments, the latter of which can accommodate the well-known phenomenon of speckle. Using one of these models for clutter together with one of several models for targets, we determine, in a range/Doppler cell, expressions for probabilities of detection of a target in the presence of clutter. It is important to control the probability of false alarms. The presence of clutter in a cell necessitates an increase in the detection threshold setting in order to control false alarms, thus lowering the probability of detection. If the clutter level is unknown, then we need to take measurements of the clutter and use it to adjust the threshold. The more clutter samples we take, the better the estimate of the clutter level and the less is the resulting detection loss. Using the expressions for the probability of detection in clutter, we can quantify the detection loss for a pair of commonly used constant false-alarm rate (CFAR) techniques and investigate how the loss varies with different parameter values, especially with regard to the number of clutter samples taken to estimate the clutter level.     

Super resolution feature extraction of moving targets

High range resolution (HRR) moving target indicator (MTI) is becoming increasingly important for many military and civilian applications such as the detection and classification of moving targets in strong clutter background. We consider the problem of extracting the HRR features of moving targets with very closely spaced scatterers in the presence of strong stationary clutter, where the range migration and Doppler frequency are taken into account. A relaxation-based algorithm, which is robust and computationally simple, is proposed to deal with the above problem. Numerical results have shown that the proposed algorithm exhibits super resolution and excellent estimation performance     

Effect of earth?s rotation and range foldover on space-based radar performance

Space-based radar (SBR) by virtue of its motion generates a Doppler frequency component to the clutter return from any point on the Earth as a function of the SBR-Earth geometry. The effect of the rotation of the Earth around its own axis also adds an additional component to this Doppler frequency. The overall effect of the rotation of the Earth on the Doppler turns out to be two correction factors in terms of a crab angle affecting the azimuth angle, and a crab magnitude scaling the Doppler magnitude of the clutter patch. Interestingly, both these quantities depend only on the SBR orbit inclination and its latitude and not on the location of the clutter patch of interest. Further, the crab angle has maximum effect for an SBR on a polar orbit that is above the equator. The crab magnitude, on the other hand, peaks for an SBR on an equatorial orbit. Together with the range foldover phenomenon, their overall effect is to generate Doppler spread/splitting resulting in wider clutter notches that degrade the clutter nulling performance of adaptive processing techniques. A detailed performance analysis and methods to minimize these effects are discussed here     

The Effect of Staggered PRF's on MTI Signal Detection

Long-range surveillance radars use MTI techniques to detect moving targets in a clutter background. The transmitter PRF is usually staggered to eliminate the blind speeds due to aliasing of the target and clutter spectra. A spectral analysis of the target and clutter signals is performed for the case of nonuniform sampling, and it is shown that the clutter spectral density continues to fold over at the basic PRF, but the signal spectrum becomes dispersed in frequency, which means that an MTI rader will never be completely blind to moving targets.     

Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter

The problem of adaptive radar detection in clutter which is nonstationary both in slow and fast time is addressed. Nonstationarity within a coherent processing interval (CPI) often precludes target detection because of the masking induced by Doppler spreading of the clutter. Across range bins (i.e., fast time), nonstationarity severely limits the amount of training data available to estimate the noise covariance matrix required for adaptive detection. Such difficult clutter conditions are not uncommon in complex multipath propagation conditions where path lengths can change abruptly in dynamic scenarios. To mitigate nonstationary Doppler spread clutter, an approximation to the generalized likelihood ratio test (GLRT) detector is presented wherein the CPI from the hypothesized target range is used for both clutter estimation and target detection. To overcome the lack of training data, a modified time-varying autoregressive (TVAR) model is assumed for the clutter return. In particular, maximum likelihood (ML) estimates of the TVAR parameters, computed from a single snapshot of data, are used in a GLRT for detecting stationary targets in possibly abruptly nonstationary clutter. The GLRT is compared with three alternative methods including a conceptually simpler ad hoc approach based on extrapolation of quasi-stationary data segments. Detection performance is assessed using simulated targets in both synthetically-generated and real radar clutter. Results suggest the proposed GLRT with TVAR clutter modeling can provide between 5–8 dB improvement in signal-to-clutter plus noise ratio (SCNR) when compared with the conventional methods.