Adaptive canceler and pulse compressor interactions

Performance results for the sidelobe level of a compressed pulse that has been preprocessed through an adaptive canceler are obtained. The adaptive canceler is implemented using the sampled matrix inversion algorithm. Because of finite sampling, the quiescent compressed pulse sidelobe levels are degraded due to the preprocessing of the main channel input data stream (the uncompressed pulse) through an adaptive canceler. It is shown that if N is the number of input canceler channels (main and auxiliaries) and K is the number of independent samples per channel, then K/N can be significantly greater than one in order to retain sidelobes that are close to the original quiescent sidelobe level (with no adaptive canceler). Also it is shown that the maximum level of degradation is independent of whether pulse compression occurs before or after the adaptive canceler if the uncompressed pulse is completely contained within the K samples that are used to calculate the canceler weights. This same analysis can be used to predict the canceler noise power level that is induced by having the desired signal present in the canceler weight calculation     

Optimal weight extraction for adaptive beamforming using systolicarrays

Systolic algorithms and architectures for parallel and fully pipelined instantaneous optimal weight extraction for multiple sidelobe canceller (MSC) and minimum variance distortionless response (MVDR) beamformer are presented The proposed systolic parallelogram array processors are parallel and fully pipelined, and they can extract the optimal weights instantaneously without the need for forward or backward substitution. We also show that the square-root-free Givens method can be easily incorporated to improve the throughput rate and speed up the system. As a result these MSC and MVDR systolic array weight extraction system are suitable for real-time very large scale integration (VLSI) implementation in practical radar/sonar system     

Coordinated adaptive beamformer over distributed antenna network

The spatial diversity of distributed network demands the individual filter to accommodate the topology of interference environment. In this paper, a type of distributed adaptive beamformer is proposed to mitigate interference over coordinated antenna arrays network. The proposed approach is formulated as generalized sidelobe canceller (GSC) structure to facilitate the convex combination of neighboring nodes’ weights, and then it is solved by unconstrained least mean square (LMS) algorithm due to simplicity. Numerical results show that the robustness and convergence rate of antenna arrays network can be significantly improved in strong interference scenario. And they also clearly illustrate that mixing vector is optimized adaptively and adjusted according to the spatial diversity of the distributed nodes which are placed in different power of received signals to interference ratio (SIR) environments.     

A new CFAR sidelobe canceler algorithm for radar

Signal or target detection is sometimes complicated by the presence of strong interference. When this interference occurs mainly in the sidelobes of the antenna pattern, a solution to this problem is realized through a sidelobe canceler (SLC) implementation. Since the false-alarm probability is a system parameter of special importance in radar, an interference-canceling technique for radar application should maintain the false-alarm probability constant over a wide range of incident interference power. With the requirements of sidelobe interference cancellation and constant false alarm rate (CFAR), a new algorithm for radar detection in the presence of sidelobe interference is developed from the generalized likelihood ratio test of Neyman-Pearson. In this development, the received interference is modeled as a nonstationary but slowly varying Gaussian random process. Cancellation of the sidelobe interference is based upon a `synchronous' estimate of the spatial covariance of the interference for the range gate being tested. This algorithm provides a fixed false-alarm rate and a fixed threshold which depend only upon the parameters of the algorithm     

Adaptive array transient sidelobe levels and remedies

The transient sidelobe level of a sidelobe canceler (SLC) is a function of the external noise environment, the number of adaptive auxiliary antennas, the adaptive algorithm used, auxiliary antenna gain margins, and the number of samples used to calculate the adaptive weights. An analytical result for the adaptive sidelobe level is formulated for the case when the adaptive algorithm is the open-loop, sampled matrix inversion (SMI) algorithm. The result is independent of whether concurrent or nonconcurrent data processing is used in the SMI algorithm's implementation. It is shown that the transient sidelobe level is eigenvalue dependent and increases proportionally to the gain margin of the auxiliary antenna elements with respect to the quiescent main antenna sidelobe level. Techniques that reduce this transient sidelobe level are discussed, and it is theoretically shown that injection independent noise into the auxiliary channels significantly reduces the transient sidelobe level. It is demonstrated that using this same technique reduces the SMI noise power residue settling time     

An anticipative adaptive array for frequency-hopping communications

To fully utilize the theoretical processing gain achievable when an adaptive array and frequency hopping are combined, frequency compensation is required. Improved versions of an anticipative adaptive array are examined that provide efficient compensation by adapting the complex weights at each antenna element to the appropriate values for a carrier frequency before that frequency is received. The underlying adaptive algorithm used is the maximum algorithm. Computer simulation results are used to compare the different versions of anticipative processing. These results show that an appropriate version ensures the rapid convergence of weights to values that provide wideband nulling of the interference and noise     

Reiterative median cascaded canceler for robust adaptive array processing

A new robust adaptive processor based on reiterative application of the median cascaded canceler (MCC) is presented and called the reiterative median cascaded canceler (RMCC). It is shown that the RMCC processor is a robust replacement for the sample matrix inversion (SMI) adaptive processor and for its equivalent implementations. The MCC, though a robust adaptive processor, has a convergence rate that is dependent on the rank of the input interference-plus-noise covariance matrix for a given number of adaptive degrees of freedom (DOF), N. In contrast, the RMCC, using identical training data as the MCC, exhibits the highly desirable combination of: 1) convergence-robustness to outliers/targets in adaptive weight training data, like the MCC, and 2) fast convergence performance that is independent of the input interference-plus-noise covariance matrix, unlike the MCC. For a number of representative examples, the RMCC is shown to converge using ~ 2.8N samples for any interference rank value as compared with ~ 2N samples for the SMI algorithm. However, the SMI algorithm requires considerably more samples to converge in the presence of outliers/targets, whereas the RMCC does not. Both simulated data as well as measured airborne radar data from the multichannel airborne radar measurements (MCARM) space-time adaptive processing (STAP) database are used to illustrate performance improvements over SMI methods.     

An Adaptive Antenna for Rejection of Wideband Interference

A modification to the adaptive array under the directional constraint [1] is proposed to improve its performance of rejecting wideband interference. By analogy to the pattern synthesis of an antenna array which produces a flat null in its radiation pattern, an additional quantity that corresponds to the derivative of the pattern is generated and combined with the standard feedback quantity to control the weights of the array. This composite system is tested by computer simulation experiments and the following points are demonstrated in contrast to the conventional, simple system: 1) faster adaptation against wideband interference, 2) remarkable improvement of the signal-to-noise ratio of the output, i. e., very small fluctuation.     

Automatic target classification of slow moving ground targets in clutter

A new approach is proposed which will allow air-to-ground target classification of slow moving vehicles in clutter. A wideband space-time adaptive (STAP) filter architecture, based on subbanding, is developed and coupled with a one dimensional template-based minimum mean squared error (MMSE) classifier. The performance of this STAP/ATC (automatic target classification) algorithm is quantified using an extensive simulation. The level of residual clutter afforded by various filter configurations and the associated incremental improvement in ATC performance is quantified, revealing the potential for realizable hardware and software implementations to achieve acceptable ATC performance.     

两种自适应方向图峰值副瓣控制方法比较

自适应阵列（或称自适应波束形成）目前已广泛应用到雷达、声纳和通信领域中用来抑制各种干扰（有意的干扰，杂波干扰和多用户干扰等）。在雷达应用中，为了减轻脉冲欺骗式干扰或旁瓣目标并利用单脉冲雷达来准确测量目标波达方向．要求自适应方向图具有低副瓣和稳定的主瓣形状。在实际应用中，各种失配误差将降低自适应阵列的性能．这些误差包括由于目标的波达方向不精确引起的信号指向误差，由通道失配和位置扰动引起的阵列校准误差和由小样本教引起的协方差矩阵估计误差。在此情况下，自适应波束形成的性能大大下降（干扰抑制性能变差。主瓣失真和高的副瓣）。已提出了一种基于二次约束的集成峰值副瓣控制（integrated peak sidelobe control，简称IPSC）方法。该方法可以精确地控制峰值副瓣电平并产生具有稳定的主瓣形状的自适应方向图。研究IPSC中目标信号的影响和信号消除方案以进一步提高IPSC的性能。并将IPSC方法和最新提出的基于二阶锥规划（second-order cone programming，简称SOCP）的分布式峰值副瓣控制（distfibuted peak sidelobe control，简称为DPSC）新方法在性能上进行了比较。仿真结果表明。在干扰抑制性能和方向图控制质量方面IPSC比DPSC性能优越。此外IPSC比DPSC计算高效。     

圆台阵列杂波模型及空时二维自适应处理

针对圆台共形阵列,建立了空时二维自适应处理(STAP)的杂波模型,给出了圆台阵列杂波抑制最优权值的计算方法。在此基础之上,为了实现可应用到实际环境中的自适应处理方法,进一步讨论了将局部联合域(JDL)降维算法推广至圆台阵列中的问题。得出了圆台阵列JDL算法降维变换矩阵的表达形式,研究了参考波束的数目选取、波束指向等因素对降维损失的影响。理论分析以及仿真结果表明,通过合理选择通道数、波束方位向指向间隔等参数,该算法能够减少自适应波束形成的计算量,而且可以用较少的训练样本获得较好的处理性能。     

Circular array STAP

Traditionally, space-time adaptive processing (STAP) for airborne early warning (AEW) radar has been applied to uniform linear arrays (ULAs). However, when considering the overall radar system, electronically scanned circular arrays have advantages: a better combination of even and continual angular and temporal coverage, and mechanical simplicity because it does not need to rotate. This paper answers the question “How well does STAP perform when applied to a circular array?” This paper shows that for the AEW mission, circular arrays are indeed STAP compatible. However, when conventional STAP algorithms are used there may be a small loss in performance when compared with a ULA. With some care in the choice and implementation of the STAP algorithm, the majority of the degradation is at close ranges, where the target returns are relatively strong. At long ranges performance is barely affected. A STAP algorithm which compensates for the circular array environment and provides better performance than existing algorithms is presented     

Eigenanalysis for interference cancellation with minimum redundancy array structure

In a previous work, the principles of the eigenanalysis method for interference cancellation was studied for uniform regular array (URA) structure, wherein the array elements are equally spaced. The main objective of this paper is to extend the results of that work to adaptive arrays with different geometry termed "minimum redundancy array" (MRA). An efficient method is presented to solve the minimum variance optimization problem and explicit analytical solutions are derived for the optimal weight vector and output noise variance of the eigencanceler. Performance analysis of the general N-element array was first derived and used to extract the performance of MRA. URA is also considered as a special case. The closed-form equation depicts the minimum variance noise residue for the single interference case, while an interactive procedure is suggested for the two interferences case. If there are more than two interferences, we propose to use direct numerical calculation.     

Numerical optimization method for array signal processing

This paper presents a novel and efficient extrema-mapping algorithm, which we call the roller-coaster algorithm. Two versions of the algorithm, the one-dimensional (1-D) and the two-dimensional (2-D) roller-coaster, are developed. Its applicability to array signal processing is demonstrated. We use it to solve a multiple source direction finding problem using multiple signal classification (MUSIC), beamformer, and minimum variance methods, and for antenna array design. The algorithm is based on heuristic assumptions and its properties are not proved. Yet, its performance was tested in many simulated experiments, yielding favorable results     

Broadband focusing for partially adaptive beamforming

A broadband adaptive beamforming approach based on the concept of signal-subspace alignment is formulated and contrasted with the conventional approach. The proposed method involves a preprocessor that focuses the signal spaces at different frequencies to a common one and a narrowband beamformer following the preprocessor. The merits that result as a consequence are partial adaptivity due to single frequency weights and decorrelation of coherent signals thus combating signal cancellation. The latter effect is studied by deriving expressions for the desired-signal distortion in a minimum variance distortionless response (MVDR) beamformer and analyzing them. Implementation issues of the preprocessor are addressed. Simulation results confirm the utility of the focusing preprocessor     

STAP for GPS receiver synchronization

A space-time adaptive processing (STAP) algorithm for delay tracking and acquisition of the GPS signature sequence with interference rejection capability is developed. The interference can consist of both broadband and narrowband jammers, and is mitigated in two steps. The narrowband jammers are modelled as vector autoregressive (VAR) processes and rejected by temporal whitening. The spatial ing is implicitly achieved by estimating a sample covariance matrix and feeding its inverse into the extended Kalman filter (EKF). The EKF estimates of the code delay and the fading channel are used for a t-test for acquisition detection. Computer simulations demonstrate robust performance of the algorithm in severe jamming, and also show that the algorithm outperforms the conventional delay-locked loop (DLL).     

Power Inversion Array in a Rotating Source Environment

The steady state performance of the Frost power inversion array is evaluated, assuming constant rotational velocity of the external noise environment in the sin ? domain. The weight vector is solved implicitly in terms of a linear matrix equation. Approximate criteria are derived for weight vector and output power deviation from optimal values, which are then applied to determine the maximum scan rate of a radar sidelobe canceler.     

Space-time adaptive processing and adaptive arrays: specialcollection of papers

Space-time adaptive processing (STAP) and related adaptive array techniques hold tremendous potential for improving sensor performance by exploiting signal diversity. Such methods have important application in radar, sonar, and communication systems. Recent advances in digital signal processing technology now provide the computational means to field STAP-based systems. The objective of this special collection of papers is to examine the current state-of-the art in STAP technology and explore the remaining obstacles, practical issues and novel techniques required to implement STAP-based radar, sonar or communication systems     

Effects of finite weight resolution and calibration errors on theperformance of adaptive array antennas

Adaptive antennas are now used to increase the spectral efficiency in mobile telecommunication systems. A model of the received carrier-to-interference plus noise ratio (CINR) in the adaptive antenna beamformer output is derived, assuming that the weighting units are implemented in hardware, The finite resolution of weights and calibration is shown to reduce the CINR. When hardware weights are used, the phase or amplitude step size in the weights can be so large that it affects the maximum achievable CINR. It is shown how these errors makes the interfering signals “leak” through the beamformer and we show how the output CINR is dependent on power of the input signals. The derived model is extended to include the limited dynamic range of the receivers, by using a simulation model. The theoretical and simulated results are compared with measurements on an adaptive array antenna testbed receiver, designed for the GSM-1800 system. The theoretical model was used to find the performance limiting part in the testbed as the 1 dB resolution in the weight magnitude. Furthermore, the derived models are used in illustrative examples and can be used for system designers to balance the phase and magnitude resolution and the calibration requirements of future adaptive array antennas     

NEW METHOD FOR REDUCED RANK STAP—NON CLUTTER CHANNEL METHOD

Space- time adaptive processing(STAP) is aleading technology candidate for improving detec-tion performance of advanced airborne early warn-ing radar.In practical radar systems,the optimumfully adaptive space- time processing[1] cannot al-ways be implemented because of the computationalcomplexity,so the design of suboptimum proces-sors has been one of the key topics in STAP.Sev-eral reduced- rank STAP methods have been pro-posed in recent years.For example,based on thegeneralized sidelobe…