Sensitivity of MIMO STAP Radar with Waveform Diversity

Space-time adaptive processing (STAP) is an effective method adopted in airborne radar to suppress ground clutter. Multiple-input multiple-output (MIMO) radar is a new radar concept and has superiority over conventional radars. Recent proposals have been applying STAP in MIMO configuration to the improvement of the performance of conventional radars. As waveforms transmitted by MIMO radar can be correlated or uncorrelated with each other, this article develops a unified signal model incorporating waveforms for STAP in MIMO radar with waveform diversity. Through this framework, STAP performances are expressed as functions of the waveform covariance matrix (WCM). Then, effects of waveforms can be investigated. The sensitivity, i.e., the maximum range detectable, is shown to be proportional to the maximum eigenvalue of WCM. Both theoretical studies and numerical simulation examples illustrate the waveform effects on the sensitivity of MIMO STAP radar, based on which we can make better trade-off between waveforms to achieve optimal system performance.     

Ambiguity resolution of multiple targets using pulse-Dopplerwaveforms

To cancel clutter, both medium-PRF waveforms which are ambiguous in both range and Doppler and high-PRF waveforms which are ambiguous in range but unambiguous in ambiguities, a previous paper has shown that superior results for a single target can be achieved by using a clustering algorithm. Here, the problem of multiple targets is considered. A maximum likelihood (ML) technique which incorporates the clustering algorithm is developed for the multiple target problem. Simulation results show that four targets which have the same speed but are at different ranges can be resolved by using a medium-PRF waveform and employing the ML resolution technique     

Doppler Processor Rejection of Range Ambiguous Clutter

Doppler processors are used in radar to separate target returns from clutter. When the clutter is at a range farther than the unambiguous range of the radar, the ability to reject the clutter is degraded. In this article the degradation is analyzed for an N-pulse batch processor with Dolph weighting, and the results show how degradation varies with design sidelobe level.     

Clutter Suppression by Complex Weighting of Coherent Pulse Trains

Uniform coherent pulse trains offer a practical solution to the problem of designing a radar signal possessing both high range and range-rate resolution. The Doppler sensitivity provides some rejection of off-Doppler (clutter) returns in the matched filter receiver. This paper considers the use of a processor in which members of the received pulse train are selectively weighted in amplitude and phase to improve clutter suppression. The techniques described are particularly suitable for rejecting interference entering the processor through ambiguous responses (range sidelobes) of the signal. The complex weights which are derived are optimum in the sense that they produce the maximum clutter suppression for a given detection efficiency. In determining these weights, it is assumed that the distribution of clutter in range and range rate relative to targets of interest is known. Thus, clutter suppression is achieved by reducing the sidelobe levels in specified regions of the receiver response. These techniques are directly applicable to array antennas; the analogous antenna problem would be to reduce sidelobe levels in a particular sector while preserving gain. Complex weighting is most successful when the clutter is limited in both range and velocity.     

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.     

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.     

Design of Optimal Radar Signals Subject to a Fixed Amplitude Constraint

The problem of designing finite-pulse-train radar signals and receivers to maximize the detectability of targets masked by thermal noise and clutter returns is considered in this paper. A practical constraint is introduced: the amplitude of each subpulse in the transmit waveform is taken to be fixed. The need for such a constraint is dictated in most radar applications, because the transmitter is most efficiently utilized by saturating its amplifying tube. An algorithm for generating optimal waveforms subject to this new constraint is presented, and the performance of the resulting waveforms is compared with those obtained using existing optimization techniques.     

Adaptive Clutter Filtering Using Autogressive Spectral Estimation

A new adaptive filter to reject clutter is derived using autoregressive spectral analysis techniques. The adaptive filter performs open. Ioop processing, resulting in a shorter transient response, and is therefore suitable for radar waveforms containing only a small number of samples. A number of examples including application to ballistic missile defense are presented to demonstrate the performance capabilities of the new adaptive filter.     

基于OTR和SHT的射频隐身雷达信号设计

为了提高雷达的射频(RF)隐身性能,结合最优匹配照射-接收机(OTR)理论与序贯假设检验(SHT)方法,提出了一种新的射频隐身雷达信号设计方法。通过发射信号了解外界环境信息,然后反馈这些信息给雷达系统,系统根据这些信息自适应设计雷达发射信号,形成一个闭环系统。以雷达目标识别为具体应用,实验仿真表明,设计的雷达信号自适应变化,减小了信号间的相关性,并且减少了照射次数,降低了辐射功率,从而实现了雷达系统的射频隐身性能。     

New correlated MIMO radar covariance matrix design with low side lobe levels and much lower complexity

In this paper, a new correlated covariance matrix for Multi-Input Multi-Output (MIMO) radar is proposed, which has lower SideLobe Levels (SLLs) compared to the new covariance matrix designs and the well-known multi-antenna radar designs including phased-array, MIMO radar and phased-MIMO radar schemes. It is shown that Binary Phased-Shift Keying (BPSK) waveforms that have constant envelope can be used in a closed-form to realize the proposed covariance matrix. Therefore, there is no need to deploy different types of radio amplifiers in the transmitter which will reduce the cost, considerably. The proposed design allows the same transmit power from each antenna in contrast to the phased-MIMO radar. Moreover, the proposed covariance matrix is full-rank and has the same capability as MIMO radar to identify more targets, simultaneously. Performance of the proposed transmit covariance matrix including receive beampattern and output Signal-to-Interference plus Noise Ratio (SINR) is simulated, which validates analytical results.     

一种基于角度-多普勒补偿的均匀圆形天线机载雷达杂波抑制方法

采用均匀圆形相控阵天线的机载雷达杂波分布随距离变化而变化,各距离单元的杂波不再满足独立同分布的条件,造成统计型空时自适应处理(STAP)器性能下降。基于此,本文建立了均匀圆形天线机载雷达模型,对其杂波分布进行了分析,得出了空间角随阵元数非线性变化的特性造成其杂波距离维分布非均匀的结论。研究了一种均匀圆形天线机载雷达杂波抑制方法,该方法先通过修正的角度 多普勒补偿(MADC)预处理消除在杂波谱中心处的非均匀,再利用基于导数更新(DBU)技术进一步减小在其他方位杂波的非均匀程度。仿真结果表明了该方法的有效性。     

High Power Radar Implementation of Coherent Waveforms

The radar use of coherent burst waveforms to obtain clutter suppression is summarized and problems arising from the high power implementation of such waveforms are discussed. These problems arise from the nonlinear nature of the typical high power radar transmitter and result in loss of subpulse-to-subpulse amplitude and phase accuracies, causing clutter suppression degradation. adaptive control loop used to measure transmission errors and provide continuous updating to minimize such errors is proposed. Residual transmission errors resulting via use of the control loop are calculated and shown to have an insignificant effect upon the clutter suppression properties of the coherent waveform. Experimental verification of control loop performance is presented.     

Automated Tracking for Aircraft Surveillance Radar Systems

An improved moving target detector (MTD) (a digital signal processor) has been designed, constructed, and tested which successfully rejects all forms of radar clutter while providing reliable detection of all aircraft within the coverage of the radar. The MTD is being tested on both terminal and enroute surveillance radars for the FAA. This processor has been integrated with automatic tracking algorithms to give complete rejection of ground clutter, heavy precipitation, and angels (birds).     

Radar Waveform Selection-A Simplified Approach

Radar measurement and resolution performance, as well as target detection in clutter, depend largely on the transmitted waveform. This explains the sizable effort that has gone into studies of radar waveforms, including attempts at the synthesis of optimum waveforms. This paper shows that, despite the unlimited variety of radar signals, waveform selection is a straightforward process. There are only four classes of waveforms, each with distinct resolution properties. When the target environment is analyzed for a particular application, it is rather evident which of these classes will fit the situation best. Choice of the specific waveform within the selected class then is merely a matter of practical implementation. Although the facts used in developing the unified theory of this paper are not new, it is demonstrated that these facts can be combined into an extremely simple theory of waveform design. Much of today's work is guided by past approaches to a particular problem, and when a design is completed there may be a question as to how close to the optimum it is. The theory presented here permits a systematic approach to waveform selection, with the important benefit that the designer knows exactly where and how much he may have deviated from the best design, and why this was done.     

Adaptive imaging for forward-looking ground penetrating radar

Most of the current forward-looking ground-penetrating radar (FLGPR) systems use conventional delay-and-sum (DAS) based methods to form radar images for detection of the target (such as a landmine). However, DAS is a data-independent approach which is known to suffer from low resolution and poor interference and clutter rejection capability. We present a data-adaptive imaging approach for FLGPR image formation based on APES (amplitude and phase estimation) and rank-deficient RCB (robust Capon beamforming). Due to the data-adaptive nature of both APES and RCB, our approach has better resolution and much better interference and clutter rejection capability than the standard DAS-based imaging methods. The excellent performance of the proposed method is demonstrated using experimental data collected via two FLGPR systems recently developed by PSI (Planning Systems, Inc.) and SRI (Stanford Research Institute).     

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.     

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.     

The Effect of Spectral Shape on Clutter Standard Deviation

Many radar systems now employ wideband waveforms and noncoherent averaging techniques to reduce the scintillation of the backscatter from ground clutter. The purpose of this paper is to quantify the effects of the wideband spectral shape on the clutter standard deviation after noncoherent averaging of the received signal. Relationships are developed which quantify the clutter standard deviation for any spectral shape and any ratio of transmitted band-width to processed bandwidth.     

Spectral Analysis and Subtraction of Noise in Radar Signals

A new method of maximum entropy spectral estimation called the revised maximum entropy method (MEM) is formulated and is applied to the spectral analysis of the echo signals from atmospheric turbulence observed by an incoherent scatter radar. The revised MEM is shown free from many demerits of the other methods for spectral analysis. Further it makes it possible to subtract the white noise usually contained in the data during the processing. Some examples of spectral estimation are shown for the actual radar signals and the simulated data. Another application of the revised MEM is the subtraction of the clutter component which is difficult to do by linear filtering. The method is successfully applied to several data abounding with the clutter to obtain the spectra of the echo signals with less clutter distortion.     

Robust space-time adaptive processing for airborne radar in nonhomogeneous clutter environments

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.