Range walk and array rotation in space-time adaptive processing:effects and compensations

This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.

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.

Direct data domain approach to space-time adaptive processing

In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.

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.

W ideband interference suppression based on space-time filter

Based upon the diagonal loading technique and the structure of the space-time adaptive processors, a novel anti-jamming method of satellite navigation is proposed. According to matrix in- verse theorem, the range of the diagonal loading values for space-time adaptive wideband signal pro- cessing structure is deduced, and the optimum equation of diagonal loading beam forming algorithm of space-time structure is obtained. Then, by the analysis of two-dimensional oriented vector in di- rection of the perturbation interference, the wideband interference covariance matrix obtained in the weights training period is modified. Finally, the optimum weight of multi-linear constrained space- time adaptive beam-forming alogrithm is derived for anti-interference filter processing. The new method effectively widens the null steering beams tion results prove the robustness of the proposed when discrepancy happens. The computer simula- method.

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.

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。

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。

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.

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.

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.

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.

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 DOPPLER WARPING METHOD FOR AIRBORNE RADAR WITH NON-SIDELOOKING ARRAY

Traditional range-dependency compensation space time adaptive processing(STAP)methods usually involve aligning the clutter spectrums in a certain point to reduce the clutter non-homogeneity.A novel compensation STAP method is proposed as an improved Doppler warping(DW)method for airborne radar with non-sidelooking radar.This method facilitates DW method to bring clutter spectrum of different range gates together in the mainlobe and subsequently compensation to accomplish space angle of different range gates alignment at multiple Doppler bins.Simulation results show that the proposed method can further reduce the clutter non-homogeneity of non-sidelooking array and significantly outperform traditional algorithms with only a little increase of the computation load.

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.

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-difference 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.

Robust two-stage reduced-dimension STAP algorithm andits performance analysis

A new two-stage reduced-dimension space-time adaptiveprocessing （STAP） approach, which combines the subcoherentprocessing interval （sub-CPI） STAP and the principalcomponent analysis （PCA）, is proposed to achieve a more enhancedconvergence measure of effectiveness （MOE）. Furthermore,in the case of the subspace leakage phenomenon, theproposed STAP method is modified to hold the fast convergenceMOE by using the covariance matrix taper （CMT） technique. Bothsimulation and real airborne radar data processing are providedto analyze the convergence MOE performance of the proposedSTAP methods. The results show the proposed method is moresuitable for the practical radar applications when compared withthe conventional sub-CPI STAP method.