CFAR detection of weak target in clutter using chaos synchronization

In this paper, a novel constant false alarm rate (CFAR) approach for detecting weak targets in sea clutter spectrum based on chaos synchronization is proposed. The weak target signal is detected when the synchronization between two identical chaotic systems is realized, even if the target spectrum lies inside the clutter spectrum. The threshold for the proposed CFAR detection is derived theoretically. The proposed chaos‐synchronization‐based CFAR technique is shown to be able to enhance the detectability of the target when the signal‐to‐clutter ratio and signal‐to‐noise ratio are low. Numerical experiments based on real radar sea clutter data confirm the effectiveness of the proposed chaos‐synchronization‐based CFAR detection method. The performance is superior to those of the standard autoregressive estimation‐based and the cell‐averaging CFAR detectors. Copyright © 2007 John Wiley & Sons, Ltd.     

一种改进的自适应恒虚警检测器

为了解决传统自适应恒虚警检测器在多目标环境下检测性能下降的问题,对传统基于指数变换的恒虚警检测器 (Variability Index CFAR,VI-CFAR)的选择策略进行改进,提出了一种改进的自适应恒虚警检测器-VIHCES-CFAR。在杂波边缘环境下和多目标干扰环境下分别选择非均匀杂波估计恒虚警检测器 (Heterogeneous Clutter Estimating CFAR,HCE-CFAR)和交互式恒虚警检测器 (Switching CFAR,S-CFAR)进行处理,提高了多目标环境下的目标检测能力,有效避免了目标遮蔽的问题。实验结果表明,在检测概率为0.5的条件下VIHCES-CFAR的信噪比相对于SVI-CFAR低0.05dB,在多目标环境下检测概率为99.78%,在杂波边缘环境下检测概率控制在10-4左右,具有稳定的抗干扰能力和良好的虚警控制能力。并通过实测数据验证了VIHCES-CFAR检测器在解决目标遮蔽问题上的有效性。     

基于改进Kalmus滤波的悬停无人机检测技术

针对复杂杂波环境下悬停无人机检测问题，提出了一种改进的Kalmus滤波 剩余回波时域均值相消 自适应CFAR联合处理算法，对无人机微多普勒检测，实现空管监视目的。通过改进的Kalmus滤波器进行频域滤波，同时对目标回波高频信号和零频信号抑制，并提高零频附近微多普勒信号增益。采用剩余回波均值相消进行二次滤波，提高无人机高速旋翼的多普勒特征信号信噪比，采用短时傅里叶算法检测目标区域多普勒变化，最后通过恒虚警处理，进一步抑制杂波，提取微多普勒信息。试验结果表明本文算法可以对悬停无人机的旋翼多普勒特征进行有效检测，目标多普勒信号幅值提升了约20 dB，实现低空监视管控目的。     

基于隐马尔可夫模型的MIMO雷达目标检测

MIMO雷达是一种新体制雷达,相对于传统雷达在目标检测及参数估计性能都有很大提高。本文针对MIMO雷达的发射信号特点及天线阵元布置特点,分析了雷达目标和杂波的散射特点。目标回波的各向异性比杂波更强。因此可以用隐马尔可夫模型（HMM）对目标和杂波分别建模,实现目标和杂波的分离。在检测过程中,首先用样本模型对HMM进行训练,得出它的参数。然后用训练好的HMMs分别对待检测信号进行归类,分别计算它属于杂波和目标的概率,计算概率比值,大于门限判断有目标。仿真实验表明,本文方法的检测性能优于传统的检测方法。本方法在检测时候的计算量很小,有利于信号的实时处理。     

基于剪切波变换的SAR图像舰船检测

针对强噪声背景下合成孔径雷达图像中舰船检测困难的问题,提出了基于剪切波(Shearlet)变换舰船检测方法。首先利用Shearlet变换分解原图像;然后根据Shearlet高频系数在目标区域和背景区域具有不同的表现性质,将多方向多尺度的Shearlet系数进行融合,实现了噪声抑制和舰船目标增强;最后采用阈值方法分割出舰船目标。实测SAR图像数据的实验表明,所提出的检测方法在强噪声背景下,相对于传统恒虚警率方法和基于小波加强的方法,能够达到较高的检测概率和较低的虚警率。     

动态杂波条件下非合作辐射源目标检测研究

针对非合作雷达辐射源采用不可控的第三方辐射源导致杂波趋于复杂的问题,提出了根据杂波协方差矩阵特点进行杂波动态化的方法,设计了对杂波动态化处理的非合作雷达辐射源目标检测系统。结果显示：所设置的辐射源与目标信息在杂波动态化处理后,可以通过非合作雷达辐射源目标检测系统提取到准确的辐射源、目标的位置、速度、角度信息。结果表明该动态化杂波不会轻易淹没功率较大的目标,该目标检测系统可以对目标进行数据采集处理,且位置速度误差均不超过1%,对目标跟踪、实际情况下的雷达信号处理有参考作用。     

一种处理非均匀分布的杂波样本的新算法

本文从理论上分析了杂波样本沿距离单元均匀分布时杂波协方差矩阵为Hermite矩阵、块Toeplitz矩阵和Toeplitz块矩阵的性质.根据此性质,提出了一种空时自适应非均匀处理新方法--均匀逼近法来处理机载相控阵雷达采集到的沿距离单元非均匀分布的杂波样本.该方法能有效地消除样本非均匀带来的影响,具有采样要求低、稳健性强、工程实现方便等特点.数值仿真结果验证了该方法的有效性.     

Highly robust ground moving target detection and relocation method for distributed satellites

The performance of ground moving target detection for distributed satellites will be affected significantly when there is an image registration error, clutter decorrelation and array error. In this paper, a new approach to moving target detection and relocation is proposed based on multi-channel and multi-pixel adaptive signal processing in an image domain. First, multichannel and multi-pixel joint data are equated to a simple array model. Given that there is an image registration error, the real steering vector of the moving target can be estimated through a space projection approach. The optimal beam forming approach is used to cancel clutter, and at the same time the cross-track velocity of the moving target can be determined by searching for the peak value of the cost function. The moving target can then be relocated on the SAR image. The simulation results indicate that this method has a good robustness to image registration error, clutter decorrelation and array error. The detection performance and the estimation accuracy are significantly improved. __________ Translated from Acta Electronica Sinica, 2007, 35(6): 1009–1014 [译自: 电子学报]     

自适应杂波滤波器设计

针对目前杂波滤波器设计存在的不足,从雷达信号处理的角度探讨了级联情况下自适应杂波抑制器的设计,提出了基本权库加相移因子的设计方法。重点分析了参差重复频率时权值的确定,并通过仿真验证了该设计方法的可行性和有效性。     

Numerical modeling of a CMOS UV/blue photodetector based on MOSFET and lateral photosensitive diode

A complementary metal‐oxide semiconductor photodetector with ring‐shaped structure is presented in this paper, which consists of a p‐channel metal‐oxide‐semiconductor field‐effect transistor and lateral photodiodes and can be applied for ultraviolet (UV)/blue detection. The p‐channel metal‐oxide‐semiconductor is enclosed by ring‐shaped lateral photodiodes and lateral ring‐shaped photodiodes for enlarging near‐surface depletion region of the photodetector. Photoelectric conversion process of the photodetector has been modeled, and some performance parameters of photodetector have been derived and evaluated. The simulation results show that the photodetector can exhibit a high current responsivity of 1 × 10⁻³ Å even for ultra‐weak light such as 0.01 μW. The composite photodetector is fabricated in a standard 0.18 µm complementary metal‐oxide semiconductor technology. The test results reveal that the presented photodetector, which just like predicted by the model, is an effective way to solve the low response of silicon‐based UV detector. In a word, the presented photodetector has a big potential application value in weak light and UV/blue light detection. Copyright © 2015 John Wiley & Sons, Ltd.     

海杂波背景下的PSO-RBF弱目标检测

海杂波背景下的目标检测是海面雷达信号处理的重要组成部分。海杂波中弱目标的检测，传统方法是基于海杂波统计特性，但是统计特性并不能很好地反映海杂波的内在动力学特性，因此检测效果很不理想。本文根据海杂波的混沌特性，对其进行了相构空间重构，并将粒子群算法算法(PSO)应用到径向基函数(RBF)神经网络核函数参数的优化学习中，利用加拿大McMaster大学采用IPIX雷达在Dartmouth地区海域实测带有目标的海杂波数据对此方法进行验证。结果表明，在混沌海杂波背景下PSO-RBF小目标检测法具有良好的预测性，相比于一般的径向基神经网络，改进算法不仅收敛速度快，且误差精度高。     

毫米波雷达海雾观测数据中的舰船杂波分析

海雾探测雷达由于架设高度低、观测仰角低,会受到众多来源的杂波干扰,这些杂波的分析是改善海雾探测效果的基础。本文针对毫米波海雾探测雷达数据中的舰船杂波,统计了舰船所造成杂波的时域及频域特性,提出了舰船杂波提取算法,实现了舰船信号和气象回波的分离。在此基础上,通过剔除舰船信号后的功率谱二次识别,实现了海雾观测数据中舰船信息的抑制,提升了毫米波雷达测雾数据的质量。更进一步,通过挖掘杂波中蕴含的信息,成功提取出舰船的长度、航速、航向等多重信息。初步探究了气象雷达在舰船监测方面的应用潜力。     

恒虚警条件下线性调频连续波雷达信号的检测

线性调频连续波(LFMCW)信号是一种典型的非平稳信号,其频率随时间变化,需借助时频信号分析方法进行研究.因此本文主要目的在于通过仿真比较3种典型时频分析方法即:Wigner-Ville Hough transform(WVHT)、periodic WVHT(PWVHT)和cumulative WVHT (CWVHT)来寻找用于恒虚警率(CFAR)条件下检测LFMCW雷达信号的最优方法.首先介绍3种方法的特点,发现PWVHT算法复杂度较高;其次推导信号经过这三种变换方法后在起始频率和调制斜率处峰值的理论公式并进行仿真比较,发现当截取信号的时间大于一个信号周期并等于信号周期的整数倍时,CWVHT和PWVHT具有相同的性能且都高于WVHT;最后比较这些方法在CFAR条件下检测LFMCW雷达信号的性能,结果表明CWVHT方法在低SNR条件下有较好的检测性能.     

Sparse leaky‐LMS algorithm for system identification and its convergence analysis

In this paper, a novel adaptive filter for sparse systems is proposed. The proposed algorithm incorporates a log‐sum penalty into the cost function of the standard leaky least mean square (LMS) algorithm, which results in a shrinkage in the update equation. This shrinkage, in turn, enhances the performance of the adaptive filter, especially, when the majority of unknown system coefficients are zero. Convergence analysis of the proposed algorithm is presented, and a stability criterion for the algorithm is derived. This algorithm is given a name of zero‐attracting leaky‐LMS (ZA‐LLMS) algorithm. The performance of the proposed ZA‐LLMS algorithm is compared to those of the standard leaky‐LMS and ZA‐LMS algorithms in sparse system identification settings, and it shows superior performance compared to the aforementioned algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

Selective partial update and set‐membership improved proportionate normalized subband adaptive filter algorithms

In this article, the concept of proportionate adaptation is extended to the selective partial update (SPU) and set‐membership (SM) normalized subband adaptive filters (NSAFs), and three proportionate normalized subband adaptive filter algorithms are established. The proposed algorithms are the improved proportionate NSAF (IPNSAF), the SPU improved proportionate NSAF (SPU‐IPNSAF), and the SM‐IPNSAF which are suitable for sparse system identification. When the impulse response of the echo path is sparse, the IPNSAF algorithm has faster convergence than NSAF. The performance of IPNSAF is also suitable for dispersive impulse responses. In SPU‐IPNSAF, the filter coefficients are partially updated rather than the entire filter at every adaptation which reduces the computational complexity of IPNSAF. The SM‐IPNSAF exhibits good performance with significant reduction in the overall computational complexity compared with the ordinary IPNSAF. The simulation results show good performance of the proposed algorithms. Copyright © 2010 John Wiley & Sons, Ltd.     

脉冲多普勒雷达地杂波仿真与系统实现

针对脉冲多普勒雷达,首先介绍了雷达杂波模拟器中地杂波的仿真模型,并对地杂波采用零记忆非线性变换(ZMNL)的方法进行仿真.同时给出了雷达信号模拟器的总体结构和硬件系统实现方案,本文构成通用的脉冲多普勒雷达信号模拟器可应用于对脉冲多普勒雷达信号的模拟,并取得了较好的效果.     

时空相干相关K分布海杂波仿真

海杂波通常会制约雷达对目标的检测,它的精确仿真关乎到雷达性能预估的准确性.首先介绍了海杂波的幅度统计模型,然后对它的时间相关性与空间相关性进行讨论.并在此基础上研究了基于球不变随机过程法(SIRP)仿真时空相干相关K分布杂波的方法.最后仿真生成海杂波数据,结果表明用该方法获到的杂波数据的概率密度函数与K分布模型匹配得很好.同时时间与空间相关性得到了满足,与杂波的复合散射机理也贴合,证实该仿真方法是可行的.     

Adaptive two‐stage Kalman filter in the presence of unknown random bias

The well‐known conventional Kalman filter gives the optimal solution but requires an accurate system model and exact stochastic information. In a number of practical situations, the system model has unknown bias and the Kalman filter with unknown bias may be degraded or even diverged. The two‐stage Kalman filter (TKF) to consider this problem has been receiving considerable attention for a long time. Until now, the optimal TKF for system with a constant bias or a random bias has been proposed by several researchers. In case of a random bias, the optimal TKF assumes that the information of a random bias is known. But the information of a random bias is unknown or incorrect in general. To solve this problem, this paper proposes two adaptive filters, such as an adaptive fading Kalman filter (AFKF) and an adaptive two‐stage Kalman filter (ATKF). Firstly, the AFKF is designed by using the forgetting factor obtained from the innovation information and the stability of the AFKF is analysed. Secondly, the ATKF to estimate unknown random bias is designed by using the AFKF and the performance of the ATKF is verified by simulation. Copyright © 2006 John Wiley & Sons, Ltd.     

Steiglitz–McBride adaptive notch filter based on a variable‐step‐size LMS algorithm and its application to active noise control

This paper proposes a new Steiglitz–McBride (SM) adaptive notch filter (SM‐ANF) based on a robust variable‐step‐size least‐mean‐square algorithm and its application to active noise control (ANC). The proposed SM‐ANF not only has fast convergence but also has small misadjustment. The variable‐step‐size algorithm uses the sum of the squared cross correlation between the error signal and the delayed inputs corresponding to the adaptive weights. The cross correlation provides robustness to the broadband signal, which plays the role of noise. The proposed SM‐ANF is computationally simpler than the existing Newton/recursive least‐squares‐type ANF. The frequency response of the new SM‐ANF has a notch depth of about ?25 dB (for each of the three frequencies considered) and has spectral flatness within 5 dB (peak to peak). This robust notch filter algorithm is used as an observation noise canceller for the secondary path estimation of an ANC system based on the SM method. The ANC with proposed SM‐ANF provides not only faster convergence but also an 11‐dB improvement in noise attenuation over the SM‐based ANC without such a SM‐ANF. Copyright © 2015 John Wiley & Sons, Ltd.     

Design of a near‐optimal adaptive filter in digital signal processor for active noise control

Adaptive filter has been applied in adaptive feedback and feedforward control systems, where the filter dimension is often determined by trial‐and‐error. The controller design based on a near‐optimal adaptive filter in digital signal processor (DSP) is developed in this paper for real‐time applications. The design integrates the adaptive filter and the experimental design such that their advantages in stability and robustness can be combined. The near‐optimal set of controller parameters, including the sampling rate, the dimension of system identification model, the dimension (order) of adaptive controller in the form of an FIR filter, and the convergence rate of adaptation is shown to achieve the best possible system performance. In addition, the sensitivity of each design parameter can be determined by analysis of means and analysis of variance. Effectiveness of the adaptive controller on a DSP is validated by an active noise control experiment. Copyright © 2007 John Wiley & Sons, Ltd.