Detection Algorithm for LFM Echo of Underwater Moving Targets Based on Discrete Fractional Fourier Transform

The mismatch between echo and replica caused by underwater moving target（UMT）＇s radial velocity degrades the detection performance of the matched filter（MF） for the linear frequency modulation（LFM） signal. By using the focusing property of fractional Fourier transform（FRFT） to that signal, a detection algorithm for UMT＇s LFM echo based on the discrete fractional Fourier transform（DFRFT） is proposed. This algorithm is less affected by the target＇s radial velocity compared with the other MF detection algorithm utilizing zero radial velocity replica（ZRVR）, and the mathematical relation between the output peak positions of these two algorithms exists in the case of existence of target echo. The algorithm can also estimate the target distance by using this relation. The simulation and experiment show that this algorithm＇s detection performance is better than or equivalent to that of the other MF algorithm utilizing ZRVR for the LFM echo of UMT with unknown radial velocity under reverberation noise background.     

Real-time Extraction of Target Position Information Based on Bi-orthogonal Wavelets

Extraction of flying target position information is the prerequisite for passive infrared guided missiles to track the target. The existing missile detection system senses the target＇ s infrared radiation, and then the generated signal is sent to signal processing circuits for extracting the target position information. In order to improve anti-interference capacity of the detection system, an algorithm of module maximum edge detection based on the bi-orthogonal wavelets is proposed to replace its hardware. The signal can be decomposed in one layer, only its high frequency detail is reconstructed. After some calculations, the average target position can be obtained. The algorithm＇s real-time implementation with DSP is also discussed. To reduce the execution time, the program structure can be optimized with double buffers in memory. This im- plementation is verified by simulations. The results show that the method has only a small amount of calculations, can meet the requirements for finding out the target position in real-time and needs not the traditional processing circuit.     

A Classification Algorithm for Ground Moving Targets Based on Magnetic Sensors

A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.     

Research of the Adaptive Beamformer Based on the Frequency Energy Normalization

An algorithm of broadband minimum variance distortionless response （MVDR） based on the frequency energy normalization is proposed. First, every narrowband frequency component of the broadband signal is normalized by the total narrowband energy of all array elements, and the narrowband power is calculated by MVDR. Finally, final spatial energy spectrum can be obtained by averaging or summing all results of every narrowband frequency bin. Any prior-information about the noise or the signal is unnecessary for the proposed method in this paper. The processing gain of the proposed method compared to the conventional broadband MVDR can be obtained as long as the amplitude fluctuation of the array noise frequency spectrum is severer than that of the target signal. The validity of the method is validated by the optimal signal detection theory. Simulation and real data are used to validate the performance of the method. Analysis results show that about 4 dB processing gain compared to the general broadband MVDR can be reached by the proposed method.     

Pautomatic Sea Target Detection Based on Wavelet Transform

An effective automatic target detection algorithm based on wavelet transform, which takes advantage of the localization and the orientation of wavelet analysis, is proposed. The algorithm detects the target in the vertical component of the wavelet transformation of the image. After mutual energy combination and sea clutter suppression through spatial weighting and thresholding, the target is located through maximum energy determination and its size is indicated through similarity measurement function of two overlapping windows. Experiment results show that the target can be detected by the algorithm in a single image frame and the better efficiency can be obtained also under the complicated backgrounds of existing the disturbances of cloud layer and fish scale light.     

Studies on the High Resolution DOA Estimation for UUV Based on Synthetic Aperture Technique

To increase the limited spatial processing gain of physical aperture of UUV （unmanned underwater vehicle） linear array and satisfy the demand of long distance target detection, a flank array based on the synthetic aperture technique is introduced into UUV, and a modified beam domain passive synthetic aperture processing algorithm （BDPSA） suitable for the flank array is proposed concurrently, which sums the beamforming of linear array coherently for successive measurement after phase compensation to make the beam output peak corresponding to the expected target bearing, expand the array aperture effectively and improve the resolution. The simulation of detection probability and distinguishing probability for double targets within 1, 1/2, 1/3 and 1/4 beam-width shows that the method of BDPSA has lower SNR threshold for target distinguishing, improves the detection probability and distinguishing probability under low SNR, and realizes the long-distance and high resolution bearing estimation because of the obvious improvement of the spatial array gain.     

Analysis on Spiral Search Pattern for Moving Target

The distribution function of the target moving in constant velocity and linear course and its meeting condition to the searcher are analyzed.Another proof method for spiral search pattern is presented and the mathematic model of the target possible position is established when performing the linear search.Base on them,the wrong idea about the spiral search pattern can be avoided.     

An Effective Method of Threshold Selection for Small Object Image

The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.     

Unobservable Problem of Target Tracking with Bearing-only Measurements in 3-dimensional Space

The bearings-only tracking （BOT） system is said to be observability if and only if the target motion parameters can be uniquely determined by noise-free bearing measurements. By utilizing the method of orthogonal vectors and charac- teristic of linear matrix equation, the problem of observability for BOT in noise-free bearings measurements from single ob- server is discussed based on the target and observer traveling in the 3-dimensional space. A proposition that BOT for target and observer traveling in the 3-dimenslonal space with constant acceleration remains unsolvable is presented and proved. By proving the proposition, it is also shown that some, motion parameter ratios of target can be estimated under certain condition satisfied by measurements and time samples. The proposition is extended to arbitrary rank of manoeuvre for the observer and the target, which BOT remains unobservable property while the rank of target manoeuvre is higher than that of the observer manoeuvre. The theoretical analysis of this paper provides the guidelines for how the observer trajectory should be formulated to avoid unobservable state for BOT in practice application.     

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

We propose a target tracking method based on particle filtering（PF） to solve the nonlinear non-Gaussian targettracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering （EKF）, which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the nonGaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples （particles） to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.     

水下主动声引信回波集成检测方法

针对水下主动声引信在复杂的自然干扰下难以准确检测的问题,结合目标回波信号与混响等干扰的各种宏观和微观信息,一方面利用改进的经验模式分解方法对引信系统接收的原始信号进行处理,得到不同模态的本征模式分量,以实现目标回波与混响的分离;另一方面利用本征模式分量得到瞬时频率方差检测统计量和能量检测统计量,将瞬时频率方差检测统计量和能量检测统计量进行组合,构建集成检测器,实现对水下主动声引信的优化检测。试验结果表明,与基于常规能量检测和瞬时频率方差检测方法相比,该方法具有更好的检测性能。     

声自导鱼雷空时自适应处理

介绍了全维和降维空时自适应处理（STAP）的基本原理，通过分析鱼雷工作环境、工作方式以及数据组织方式，讨论了采用STAP方法提高声自导鱼雷混响背景下目标检测性能的可能性，给出了关键步骤的解决方案和STAP抗混响的基本流程。分析结果表明，采用STAP进行混响抑制难度要大于对机载预警（AEW）雷达杂波的抑制，然而在实现上却是可能的。仿真结果表明，采用STAP方法能够获得比常规方法更好的检测性能。STAP方法能够充分利用声自导鱼雷混响空时分布特性，是一种有前途的抑制鱼雷混响的新方法。     

不确实波导环境下基于子空间建模的恒虚警检测方法

浅海主动声纳检测与估计面临的主要问题是不确实浅海信道导致的回波信号不确实和混响干扰。为此，本文提出一种子空间回波信号的恒虚警( CFAR)检测与估计方法：对不确实浅海波导中的回波信号采用子空间信号建模方法；将混响干扰建模为一种类信号干扰，基于广义似然比检验( GLRT)的思想，将混响相关矩阵的最大似然估计代入到似然比检测中，由于GLRT具有恒虚警特性，最终得到子空间回波信号的恒虚警检测器。通过仿真和实际数据处理分析表明，这种子空间回波信号恒虚警检测器对不确实信道具有很好的相干匹配能力，对信道不确实性具有较好的宽容性，能得到较好的脉冲压缩效果，提高目标位置估计精度。较之常规匹配滤波器，其检测性能可提高1—2.5 dB.     

目标回波时频分布的几何结构图像形态特征

沉底目标识别的关键在于从混响背景中提取出稳定的目标回波信号特征。目标的棱角散射能够携带目标的几何形状信息,在时频域内具有较规则的分布特性,但是各棱角散射回波声程差小,而且淹没在混响中。已有的时频分析方法局限于其抗混响能力及时频分辨力,为得到一种有效的目标几何特征提取方法,提出将一维几何回波时域信号在二维时频域中的几何分布特征作为图像特征进行特征提取,通过研究几何亮点回波和混响在时频平面上的形态特征,构造与几何亮点时频特性匹配的结构元并对时频分布图像进行形态滤波。通过仿真与湖试数据分析,相比已有方法,文中所提方法能够在实现目标几何亮点结构的识别同时进一步抑制混响。     

一种基于快速傅里叶变换反鱼雷鱼雷主动声引信回波检测方法

为了实现反鱼雷鱼雷（ATT）声引信在强混响背景下对回波信号的检测,利用反鱼雷鱼雷主动声引信目标回波信号与混响噪声之间的特性差异,基于多普勒频移这一特征量设计了基于快速傅里叶变换（FFT）的回波信号检测方法。在降低了接收机设备量的同时,实现了-50～50 kHz的频率搜索范围。最后,通过蒙特卡罗方法仿真分析了接收系统工作特性。研究结果表明,基于FFT的反鱼雷鱼雷主动声引信检测系统可以实现对强混响背景下目标回波的检测。当信噪比高于3 dB时,在虚警概率Pf=10-4下,检测系统检测概率达到0.999 5以上。     

基于离散分数阶傅里叶变换的水下动目标线性调频回波检测算法的研究

水下动目标径向速度造成的回波和样本之间失配导致匹配滤波器对于线性调频( LFM)信号的检测性能下降。利用分数阶傅立叶变换对LFM信号的聚焦特性，提出一种基于离散分数阶傅立叶变换的水下动目标LFM回波检测算法。该算法与零速样本匹配滤波检测算法相比受目标径向速度影响较小，并且理论分析表明在目标回波存在的情况下，这两种算法输出的峰值位置之间存在数学关系。利用该数学关系本文算法同样可以估计目标距离。仿真和实验数据分析表明：本文算法在强混响噪声背景下对于径向速度未知动目标LFM回波昀检测性能优于或相当于零速样本匹配滤波。     

一种基于双极性脉冲信号的沉底及掩埋小目标探测方法

针对沉底及掩埋小目标探测需求,设计低频双极性脉冲信号,提出基于双极性脉冲信号的空间与时间（简称空时）联合探测方法。分别从频谱、模糊度函数分析探测信号,根据声纳方程分析探测沉底及掩埋目标信混比情况,并搭建试验平台,完成了探测沉底小目标的试验验证。理论分析、仿真计算及试验结果表明：低频、窄波束、小掠射角方式有利于探测沉底及掩埋小目标;低频双极性脉冲信号及空时联合探测方法作为一种新型探测信号及处理方法,可提高沉底及掩埋小目标的空间分辨能力及混响抑制性能。     

宽频带水声信号目标回波建模与仿真研究

宽频带信号的目标回波携有的目标信息量大,混响背景相关性弱,有利于目标检测、参量估计和目标特征提取,可实现目标的精确测距和测速以及目标识别。该文对宽频带水声信号目标声回波特性进行了研究,给出了海洋传输信道和目标散射信道的系统函数,在此基础上建立了宽频带目标回波模型,并进行了计算机仿真,仿真结果也显示了回波信号携有目标信息量大的特性。     

基于亮区-亮点模型的水下近场目标回波建模方法

考虑工作在近场区的水中兵器声探测系统目标特性建模的需求,提出了一种基于亮区-亮点模型的水下近场目标回波建模方法。本方法首先对目标物进行面元划分,使得每一个面元相对于换能器均工作在远场区,之后通过换能器的指向性确定目标物属于亮区的面元,最后应用亮点法对于每个面元的回波进行预测并叠加,最终获得水下近场目标物的回波信息。本文通过对椭球目标物进行建模,且模拟了其在侧弦90°入射和侧弦30°入射2种情况的回波,并与真实情况下回波信号进行对比,结果显示,采用该方法所建的模型在近场情况下可有效模拟回波的幅值、时延和脉宽等信息,并对于回波波形具有一定的模拟精度。