SPACE-TIME ADAPTIVE PROCESSING FOR AIRBORNE RADAR:A CONVENIENT IMPLEMENTATION APPROACH

A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.

PRECONDITIONED METHODS FOR SPACE-TIME ADAPTIVE PROCESSING

This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant-Block(BCCB)preconditioner is constructed.Based on thepreconditioner,a Preconditioned Multistage Wiener Filter(PMWF)which can be implemented by thePreconditioned Conjugate Gradient(PCG)method is proposed.Simulation results show that thePMWF has faster convergence rate and lower processing rank compared with the MWF.

STATISTICAL SPACE-TIME ADAPTIVE PROCESSING ALGORITHM

For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to estimate the approximative covariance matrix in the non-homogeneous condition. According to the statistical characteristics of the space-time snapshot data, via defining the aggregate snapshot data and corresponding events, the conditional probability of the space-time snapshot data which is the effective training data is given, then the weighting coefficients are obtained for the weighting method. The theory analysis indicates that the statistical methods of the Bayes and likelihood criterion for covariance matrix estimation are more reasonable than other methods that estimate the covariance matrix with the use of training data except the detected outliers. The last simulations attest that the proposed algorithms can estimate the covariance in the non-homogeneous condition exactly and have favorable characteristics.

A framework of rank-reduced space-time adaptive processing for airborne radar and its applications

A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar systems which includes most of suboptimum algorithms in the literature is proposed. The performance of two typical rank-reduced time-space joint-domain processors based on Doppler pre-filtering is analyzed in detail based on the proposed framework.

Adaptive beamforming and phase bias compensation for GNSS receiver

Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.

一种抑制严重非均匀杂波的机载MIMO-STAP方法

在机载MIMO雷达体制下,针对严重非均匀环境(包括斜视阵和前视阵近程段),提出了一种新的基于时域平滑的两级级联降维STAP方法,先后对杂波和孤立干扰进行抑制.第一级对少量独立同分布(IID)辅助样本进行平滑,用得到的所有样本估计杂波特性并用先时后空自适应级联处理器(称为mDT-SAP)中的3DT-SAP(简称3DT)方法进行抑制,第二级用待检测距离单元数据进行平滑估计孤立干扰特性并用3DT方法进行抑制.该方法克服了直接数据域(DDD)方法空时孔径损失大,误差鲁棒性差及没有充分利用统计信息的缺点,具有良好的性能.计算机仿真实验验证了其有效性和优越性.

知识辅助的机载MIMO雷达STAP非均匀样本检测方法

针对样本协方差矩阵受干扰目标污染时机载多输入多输出(multiple-input multiple-output,MIMO)雷达空时自适应处理(space-time adaptive processing,STAP)目标检测性能下降的不足,提出一种知识辅助(knowledge-aided,KA)的广义内积非均匀样本检测方法。首先利用扁长椭球波函数估计的杂波子空间知识,离线构造杂波协方差矩阵,然后与广义内积非均匀检测器(generalized inner product non-homogeneity detector,GIP NHD)结合,实现对训练样本的有效选择,使目标检测不受训练样本中干扰目标的影响。仿真结果表明,相对于常规GIP方法,KA-GIP方法能够对存在干扰目标的样本进行更加有效地剔除,并且机载MIMO雷达STAP的目标检测性能得到显著提升,因此更有利于实际工程应用。

机载雷达超低空多径目标稳健STAP方法

超低空目标与环境之间存在耦合多径效应,产生"镜像"虚假目标,严重恶化协方差矩阵估计和运动目标检测性能。针对这一问题,该文提出基于时域优化的多点联合幅相约束的稳健空时自适应处理(space-time adaptive processing,STAP)方法。基于超低空目标及其"镜像"目标多普勒扩展特性的分析,提出了目标及临近空时二维域多点联合幅相约束的STAP方法,并基于保形约束推导了时域响应的解析解,实现了STAP二维响应的主瓣保形,克服了目标多径效应造成的检测性能损失。仿真实验验证了该文方法的有效性。

基于双迭代与二阶锥规划的机载雷达稳健降维STAP方法

针对机载雷达空时自适应处理(STAP)中期望目标导向矢量的失配问题,提出一种基于双迭代与二阶锥规划的稳健降维STAP方法。该方法首先将权矢量分解为空域与时域2个低维权矢量的Kronecker积;然后,分别限定实际空域、时域导向矢量与假定导向矢量之间的误差范数边界,并通过对各自最差性能进行优化,转化为相应的SOCP形式,进而利用双迭代算法实现了对2个低维权矢量的分别求解;最终,合成全维STAP权矢量。该方法在保证稳健STAP性能的同时,通过双迭代降维处理能够有效降低训练样本数需求与运算复杂度,因此更具有实际应用价值。仿真结果验证了提出方法的有效性。

STAP method based on atomic norm minimization with array amplitude-phase error calibration

In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.

Improved STAP algorithm based on APES

Space-time adaptive processing（STAP） has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving target indication（GMTI） radar.This paper applies an amplitude and phase estimation（APES） approach to two aspects of the STAP algorithm.Firstly,APES is applied to accurately describe the clutter characteristic in angle-Doppler domain.Then,APES is incorporated into the standard STAP algorithm to improve its performance without increasing transmitting/receiving channel and pulse number.The experimental examples show that the detection performance can be improved by using the APES technique,as well as the high computational complexity can be avoided.

NEW METHOD FOR REDUCED RANK STAP—NON CLUTTER CHANNEL METHOD

For reduced-rank space-time adaptive processing(STAP) in airborne radar, this paper presents a new method — non clutter channel(NCC） method which is easy to implement in real radar systems. The NCC method uses those “channels” located in the non-clutter domain to construct the reduce-rank transformation matrix. This method avoids eigen-decomposition and the computational cost is very low. The performance is compared with that of several other methods; the simulation demonstrates that the NCC method can well approach the optimum performance and even outperform some more complex methods in low rank.

机载前视阵雷达阵元误差稳健的空时插值补偿方法

空时插值方法通过对地面杂波空时导向矢量进行插值变换,能够有效地降低机载前视阵雷达地面杂波的距离依赖性,改善空时自适应处理器的杂波抑制性能。然而,当机载雷达接收通道存在阵元误差时,该方法对接收的数据处理失效。针对该问题,提出一种稳健的空时插值方法,该方法在杂波空时导向矢量周围选取约束导向矢量,然后进行插值变换,补偿地杂波距离依赖性。仿真结果表明,当机载雷达接收通道存在阵元误差时,该方法能够有效地降低接收的地杂波数据的距离依赖性,提高空时自适应处理器的杂波抑制性能。

弹载雷达和差通道稳健自适应杂波抑制方法

当前弹载雷达普遍采用和差通道体制,在超低空目标检测应用中,由于超低空目标与地海面存在严重的电磁耦合场,形成的镜像虚假目标出现在训练样本中,会造成目标信号相消,严重恶化协方差矩阵估计和动目标检测性能。针对此问题,提出了在目标及其临近空时二维域进行幅相联合多点约束的稳健空时自适应处理(space-time adaptive processing,STAP)方法,实现了STAP二维响应的主瓣保形,克服了目标污染造成的动目标检测性能损失,提高了多普勒估计的精度和稳健性。针对弹载雷达前视阵配置带来的杂波谱扩散问题,则通过最小二乘法进行补偿。仿真实验验证了所提方法的有效性。

基于空时自适应处理技术的雷达相位编码的研究

为通过雷达编码技术可以使雷达性能得到提高。本文主要研究优化雷达相位编码使得雷达空时自适应处理器的输出信噪比最大的问题。本文考虑以下约束:保证雷达编码与已知巴克码达到一定的相似度、空间和时间多普勒频率估计准确度达到一定的要求,同时考虑到雷达能量的鲁棒性问题。对于上述非凸二次约束优化问题,我们用了快速有效的秩一分解方法。通过仿真实验可以证明,这种相位雷达编码可以使雷达性能提高。

Diagonally loaded SMI algorithm based on inverse matrix recursion

The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.

非确知先验信息条件下MIMO雷达波形设计

考虑了目标先验知识未确知条件下,提升基于多输入多输出正交频分复用(MIMO-OFDM)雷达的空时自适应处理(STAP)最差条件下检测概率的稳健波形设计问题。在发射波形恒模特性及目标参数不确定凸集约束下,基于最大化输出信干噪比(SINR)准则,构建了提高最差条件下MIMO-OFDM-STAP检测性能的极大极小波形优化问题。为求解所得NP-hard问题,先将发射波形恒模特性松弛为低峰均比约束,而后利用对角加载(DL)将其重构为可有效求解的半定规划(SDP)问题。与传统非相关信号和主流非稳健算法相比,数值仿真验证了该算法可显著提升MIMO雷达目标检测的稳健性。

An Improved Space-Time Joint Anti-jamming Algorithm Based on Variable Step LMS

In wireless communication, the space-time anti-jamming method is widely applied because it shows better performance than the pure airspace and pure temporal anti-jamming methods. However, its application is limited by its computational complexity, and it cannot suppress narrowband interference that is in the same direction as the navigation signal. To solve these problems, we propose improved frequency filter to filter the narrowband interference from the desired signal direction in advance, meanwhile, an improved variable step Least Mean Square （LMS） method is proposed to complete the space-time array weights with fast iteration, thereby reducing computational complexity. The simulation results show that, compared with conventional methods, the anti-jamming capability of the proposed algorithm is significantly enhanced; and its complexity is significantly reduced.

Target location with signal fitting and sub-aperture tracking for airborne multi-channel radar

The location of a moving target based on signal fitting and sub-aperture tracking from an airborne multi-channel radar is dealt with.The proposed approach is applied in two steps：first,the ambiguous slant-range velocity is derived with a modified single-snapshot multiple direction of arrival estimation method,and second,the unambiguous slant-range velocity is found using a track-based criterion.The prominent advantage of the proposed approach is that the unambiguous slant-range velocity can be very large.Besides,the first stage is carried out at the determinate range-Doppler test cell by azimuth searching for fitting best to the moving target signal,therefore,the location performance would not be sacrificed in order to suppress clutter and/or interference.The effectiveness and efficiency of the proposed method are validated with a set of airborne experimental data.

Improved Multistage Wiener Filters in Nonhomogeneous Clutter Environments

A new method combining space-time preprocessing with multistage Wiener filters（STPMWF）is proposed to improve the performance of space-time adaptive processing（STAP）in nonhomogeneous clutter scenario.The new scheme only requires the data from the primary range bin,thus it can suppress discrete interferers efficiently,without calculating the inverse of covariance matrix.Comparing to the original MWF approach,the proposed scheme can be regarded as practical solutions for robust and effective STAP of nonhomogeneous radar data.The theoretical analysis shows that our STPMWF is simple in implementation and fast in convergence.The numeric results by using simulated data exhibit a good agreement with the proposed theory.