Zengping Chen

Micro-Doppler Analysis and Separation Based on Complex Local Mean Decomposition for Aircraft With Fast-Rotating Parts in ISAR Imaging

In traditional inverse synthetic aperture radar (ISAR) imaging of aircraft, rigid-body motion is usually assumed, and a focused ISAR image can be obtained using the classical range-Doppler algorithm after the translational motion compensation. However, in real-world situations, nonrigid-bodies such as the fast-rotating blades, propellers or turbofans are often present in aircraft. The ISAR image of the main body will be shadowed by the micro-Doppler (m-D) induced by the rotating parts of the target, whereas the m-D parameter estimation of the rotating parts also becomes more difficult because of the interference from the main body returns. To solve this problem, the Doppler frequency difference between the main body and the rotating parts of the aircraft is analyzed and the complex local mean decomposition (CLMD) is applied to separate the m-D signature in the ISAR imaging. The CLMD method can separate the oscillation mode embedded in signals accurately and decompose the complex modulation nonstationary signals adaptively into some stable monocomponents. After the separation, better geometrical features of the main body and better m-D features of the rotating parts can be obtained by processing each independently. The results from the simulated and measured data are given to verify the validity of the algorithm proposed in this paper.

Interferometric inverse synthetic aperture radar imaging for space targets based on wideband direct sampling using two antennas

Abstract Interferometric inverse synthetic aperture radar (InISAR) imaging provides complementary information to monostatic inverse synthetic aperture radar (ISAR) imaging. This paper proposes a new InISAR imaging system for space targets based on wideband direct sampling using two antennas. The system is easy to realize in engineering since the motion trajectory of space targets can be known in advance, which is simpler than that of three receivers. In the preprocessing step, high speed movement compensation is carried out by designing an adaptive matched filter containing speed that is obtained from the narrow band information. Then, the coherent processing and keystone transform for ISAR imaging are adopted to reserve the phase history of each antenna. Through appropriate collocation of the system, image registration and phase unwrapping can be avoided. Considering the situation not to be satisfied, the influence of baseline variance is analyzed and compensation method is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Experimental results prove the validity of the analysis and the three-dimensional imaging algorithm.

Analysis of synchronization errors for InISAR on separated platforms

Bistatic inverse synthetic aperture radar (BiISAR) imaging and interferometric inverse synthetic aperture radar (InISAR) imaging can provide complementary information to monostatic inverse synthetic aperture radar (MoISAR) imaging. Time synchronization is a requirement for both systems. This paper focuses on the problem of the time synchronization in the BiISAR and InISAR imaging with a polynomial time synchronization error model (PTSEM) in theory. The effects of the time synchronization errors to the range and azimuth compression with the synchronization errors are analyzed in detail. A phase error model transferred from the synchronization errors to the interferometric error is established. A simulation displays the results of the analysis.

Robust mainlobe interference suppression for coherent interference environment

A mainlobe interference suppression method is proposed in this paper, which can still work when the signal of interest (SOI) is present in the training data. In this method, the iterative adaptive approach (IAA) is applied to spatial spectrum estimation at first. Then, IAA spatial spectrum is used to reconstruct the interference-plus-noise covariance matrix (INCM). Next, the eigenvector associated with mainlobe interference in INCM is determined, and the eigen-projection matrix can be calculated to suppress the mainlobe interference. Meanwhile, the sidelobe-interference-plus-noise covariance matrix (SINCM) can be reconstructed. Finally, the adaptive weight vector is obtained. One main advantage is that the proposed method can deal with coherent mainlobe interference and sidelobe interferences simultaneously. Simulation results demonstrate the effectiveness and robustness of the proposed method.

Parameter estimation of chirp signal under low SNR

Aiming at solving the problem of great difficulty and low accuracy existing in parameter estimation of chirp signal under low signal-to-noise ratio (SNR) condition, an algorithm of accurate parameter estimation of chirp signal is proposed. First, the algorithm extracts ridge frequency of chirp signal based on Short Time Fourier Transform. Second, the protruding glitch frequencies are eliminated through median filter with proper size and the smoothing frequencies are obtained corresponding to the time. Third, the frequency time frequency-modulated (FM) line is fitted coarsely by the least-square linear fitting method, and some frequency points are removed, which are far away from the FM line. Repeat the process several times until the sample correlation coefficient of the fitted line is in high degree when the optimum chirp line is fitted out, so chirp rate and initial frequency are obtained. Simulation shows that the correct rate of parameter estimation is very high. When SNR is not less than −17 dB, the correct rate is 100%, and when the SNR is −18 dB, the correct rate is still capable of up to 99%. This algorithm has a lower SNR threshold of about −17 dB. When the SNR is greater than threshold, parameter estimation accuracy is close to Cramer Rao low bound (CRLB), higher than parameter estimation based on the phase field method. Measured data experiments show that the algorithm can reasonably fit the chirp line of measured chirp signal, which better characterizes the FM features of chirp signal.摘要创新点针对低信噪比下线性调频(Linear Frequency Modulation, LFM)信号参数估计难度大以及精度不高的问题, 本文提出一种基于短时傅立叶变换(Short Time Fourier Transform, STFT)的最小二乘调频直线拟合的LFM信号参数估计算法。 该算法首先通过LFM信号的STFT提取出脊线频率并通过中值滤波滤除凸出的毛刺频率点, 然后通过最小二乘法粗拟合出频率-时间调频直线并剔除偏离调频直线距离较大的频率点, 迭代进行该过程多次, 直到拟合直线的样本相关程度很高, 最终拟合出最优的频率-时间直线, 从而得到调频斜率和起始频率。 仿真表明, 本算法调频斜率估计正确率较高, 信噪比不小于−17dB时, 正确率达到100%, 信噪比为−18dB时, 正确率仍能高达99%。 本算法具有较低的信噪比门限, 约为−17dB; 高于信噪比门限时, 参数估计精度接近克拉美-罗限(Cramer Rao Low Bound, CRLB), 精度高于基于相位域的参数估计方法。 实测数据实验表明, 本文算法能够合理地拟合出实测LFM信号的调频直线, 较好地表征了LFM信号的调频特征。

Interferometric ISAR imaging for space moving targets on a squint model using two antennas

This paper proposes a novel InISAR imaging method for space moving targets on a squint model using two antennas. In the pre-processing for range compression based on wideband direct sampling data, an adaptive matched filter containing speed is designed to carry out high-speed movement compensation that is essential for space targets. In order to reserve the phase history of each antenna, coherent processing for ISAR imaging is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Considering the condition may not be strictly satisfied, the influence of 3D motion and squint model is analyzed and a compensation method is adopted. Image distortion is corrected using coordinate transform. Simulation results confirm the effectiveness of the analysis and 3D imaging algorithm.

Generalized CPHD filter modeling spawning targets

In some multiźtarget tracking applications, appearing targets are suitably modeled as spawning from existing targets. However, in the original cardinalized probability hypothesis density (CPHD) filter, this type of model is not included; instead appearing targets are modeled by spontaneous birth only. Recently, two versions of CPHD filter modeling spawning targets have already been developed, but these two methods are tractable only when the spawning targets cardinality distribution is restricted to be the Bernoulli distribution, the Poisson distribution or the Zero-inflated Poisson distribution. In this paper, we derive a generalized CPHD filter which is tractable and has no constraint of the cardinality distribution of the spawning targets, that is to say, the spawning targets cardinality distribution can be arbitrary. The derivation is based on the finite set statistics (FISST) and the Faa di brunos determinant formula. Moreover, how this generalized CPHD filter degrades into the two previous versions is also given in this paper. The resulting filter is different from the original CPHD filter in two aspects: first, the prediction equation of the PHD function changes to be identical with that of the probability hypothesis density (PHD) filter; and second, the cardinality distribution prediction equation is now an expression including the cardinality distribution information of the spawning targets. Simulation results show that the proposed method can response much faster than the original CPHD filter in target number estimate when spawning targets appear, and has a much smaller cardinality estimate variance than the PHD filter and the original CPHD filter. A comparison considering the optimal sub-pattern assignment (OSPA) metric also demonstrates the good performance of the proposed method. The general explicit cardinality prediction equation for the CPHD filter modeling spawning targets is derived.The derivation is based on the famous Faa di brunos determinant formula.A tractable recursion computation technique of the general cardinality prediction equation is proposed.

Multi-target simultaneous ISAR imaging based on compressed sensing

Conventional range-Doppler (RD) inverse synthetic aperture radar (ISAR) imaging method utilizes coherent integration of consecutive pulses to achieve high cross-range resolution. It requires the radar to keep track of the target during coherent processing intervals (CPI). This restricts the radar’s multi-target imaging ability, especially when the targets appear simultaneously in different observing scenes. To solve this problem, this paper proposes a multi-target ISAR imaging method for phased-array radar (PAR) based on compressed sensing (CS). This method explores and exploits the agility of PAR without changing its structure. Firstly, the transmitted pulses are allocated randomly to different targets, and the ISAR image of each target can be then reconstructed from limited echoes using CS algorithm. A pulse allocation scheme is proposed based on the analysis of the target’s size and rotation velocity, which can guarantee that every target gets enough pulses for effective CS imaging. Self-adaptive mechanism is utilized to improve the robustness of the pulse allocation method. Simulation results are presented to demonstrate the validity and feasibility of the proposed approach.

Robust rigid coherent point drift algorithm based on outlier suppression and its application in image matching

Abstract. The typical probability based point pattern matching method is coherent point drift (CPD) algorithm, which treats one point set as centroids of a Gaussian mixture model, and then fits it to the other. It uses the expectation maximization framework, where the point correspondences and transformation parameters are updated alternately. However, the anti-outlier performance of CPD is not robust enough as outliers have always been involved in the operation until the CPD converges. Hence, an automatic outlier suppression (AOS) mechanism is proposed. First, outliers are judged by a matching probability matrix. Then, transformation parameters are fitted using accurate matching point sets. Finally, the Gaussian centroids are forced to move coherently by this transformation model. AOS-CPD can efficiently improve the anti-outlier performance of rigid CPD. Furthermore, CPD is applied to image matching. A new local changing information descriptor-relative phase histogram (RPH) is designed and RPH-AOS-CPD is proposed to embed RPH measurement into AOS-CPD as a constraint condition. RPH-AOS-CPD makes full use of grayscale information besides having an excellent anti-outlier performance. The experimental results based on both synthetic and real data indicate that compared with other algorithms, AOS-CPD is more robust to outliers and RPH-AOS-CPD offers a good practicability and accuracy in image matching applications.

Image registration of interferometric inverse synthetic aperture radar imaging system based on joint respective window sampling and modified motion compensation

Abstract We propose a new image registration method based on joint respective window sampling (RWS) and modified motion compensation (MMC) in an interferometric inverse synthetic aperture radar (InISAR) imaging system using two antennas. The causation and quantitative analysis of the offset between two ISAR images of different antennas along the baseline are analyzed. In the proposed method, the RWS method, according to the measured distance between the target and different antennas, compensates the offset in the range direction. The MMC method is adopted to eliminate the offset in the Doppler direction. Simulation results demonstrate that the offset between the two ISAR images can be compensated effectively, consequently achieving a high-quality three-dimensional InISAR image.