Automatic recognition of sonar targets using feature selection in micro-Doppler signature

Currently,the use of intelligent systems for the automatic recognition of targets in the fields of defence and military has increased significantly.The primary advantage of these systems is that they do not need human participation in target recognition processes.This paper uses the particle swarm optimization(PSO)algorithm to select the optimal features in the micro-Doppler signature of sonar targets.The microDoppler effect is referred to amplitude/phase modulation on the received signal by rotating parts of a target such as propellers.Since different targets'geometric and physical properties are not the same,their micro-Doppler signature is different.This Inconsistency can be considered a practical issue(especially in the frequency domain)for sonar target recognition.Despite using 128-point fast Fourier transform(FFT)for the feature extraction step,not all extracted features contain helpful information.As a result,PSO selects the most optimum and valuable features.To evaluate the micro-Doppler signature of sonar targets and the effect of feature selection on sonar target recognition,the simplest and most popular machine learning algorithm,k-nearest neighbor(k-NN),is used,which is called k-PSO in this paper because of the use of PSO for feature selection.The parameters measured are the correct recognition rate,reliability rate,and processing time.The simulation results show that k-PSO achieved a 100%correct recognition rate and reliability rate at 19.35 s when using simulated data at a 15 dB signal-tonoise ratio(SNR)angle of 40°.Also,for the experimental dataset obtained from the cavitation tunnel,the correct recognition rate is 98.26%,and the reliability rate is 99.69%at 18.46s.Therefore,the k-PSO has an encouraging performance in automatically recognizing sonar targets when using experimental datasets and for real-world use.

Parameter estimation for rigid body after micro-Doppler removal based on L-statistics in the radar analysis

In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Recently, L. Stankovic proposed an m-D removal method based on L-statistics, which has been proved effective and simple. The algorithm can extract the m-D effects according to different behaviors of signals induced by rotational parts and rigid bodies in time-frequency （T-F） domain. However, by removing m-D effects, some useful short time Fourier transform （STFT） samples of rigid bodies are also extracted, which induces the side lobe problem of rigid bodies. A parameter estimation method for rigid bodies after m-D removal is proposed, which can accurately re- cover rigid bodies and avoid the side lobe problem by only using m-D removal. Simulations are given to validate the effectiveness of the proposed method.

Particle swarm optimization for rigid body reconstruction after micro-Doppler removal in radar analysis

The rotating micro-motion parts produce micro-Doppler(m-D)effects which severely influence the quality of inverse synthetic aperture radar(ISAR)imaging for complex moving targets.Recently,a method based on short-time Fourier transform(STFT)and L-statistics to remove m-D effects is proposed,which can separate the rigid body parts from interferences introduced by rotating parts.However,during the procedure of removing m-D parts,the useful data of the rigid body parts are also removed together with the m-D interferences.After summing the rest STFT samples,the result will be affected.A novel method is proposed to recover the missing values of the rigid body parts by the particle swarm optimization(PSO)algorithm.For PSO,each particle corresponds to a possible phase estimation of the missing values.The best particle is selected which has the minimal energy of the side lobes according to the best fitness value of particles.The simulation and measured data results demonstrate the effectiveness of the proposed method.

DETECTION ON MICRO-DOPPLER EFFECT BASED ON LASER COHERENT RADAR

A laser coherent detection system of 1550 nm wavelength was presented, and experimental research on detecting micro-Doppler effect in a dynamic target was developed. In the study, the return signal in the time domain is decomposed into a set of components in different wavelet scales by multi-resolution wavelet analysis, and the components are associated with the vibrational motions in a target. Then micro-Doppler signatures are extracted by applying the reconstruction. During the course of the final data processing frequency analysis and time-frequency analysis are applied to analyze the vibrational signals and estimate the motion parameters successfully. The experimental results indicate that the system can effectively detect micro-Doppler information in a moving target, and the tiny vibrational signatures also can be acquired effectively by wavelet multi-resolution analysis and time-frequency analysis.

Parity recognition of blade number and manoeuvre intention classification algorithm of rotor target based on micro-Doppler features using CNN

This paper proposes a parity recognition of blade number and manoeuvre intention classification algorithm of rotor target based on the convolutional neural network(CNN) using micro Doppler features. Firstly, the time-frequency spectrograms are acquired from the radar echo by the short-time Fourier transform.Secondly, based on the obtained spectrograms, a seven-layer CNN architecture is built to recognize the blade-number parity and classify the manoeuvre intention of the rotor target. The constructed architecture contains a leaky rectified linear unit and a dropout layer to accelerate the convergence of the architecture and avoid over-fitting. Finally, the spectrograms of the datasets are divided into three different ratios, i.e., 20%, 33% and 50%,and the cross validation is used to verify the effectiveness of the constructed CNN architecture. Simulation results show that, on the one hand, as the ratio of training data increases, the recognition accuracy of parity and manoeuvre intention is improved at the same signal-to-noise ratio(SNR);on the other hand, the proposed algorithm also has a strong robustness: the accuracy can still reach 90.72% with an SNR of – 6 dB.

Micro-Doppler feature extraction of micro-rotor UAV under the background of low SNR

Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.

Modeling simulation and experiment of micro-Doppler signature of precession

Spatial precession is a special micro-motion of the spinning-directional target, and the micro-Doppler signature of the cone-shaped target with precession is studied. The micro-motion model of precession is built first, and then the micro-Doppler model is developed based on the proposed concept of micro-motion ma- trix, by which the theoretical formula of micro-Doppler signature of precession is derived. In order to further approach to the actual case, the occlusion effect is firstly considered in micro-Doppler, and the simulated result with occlusion effect is well in accordance with the measured result in microwave anechoic chamber, which suggests that the micro-motion model and micro-Doppler model of precession are both valid.

Micro-Doppler Parameter Estimation Method Based on Compressed Sensing

A micro-Doppler parameter estimation method based on compressed sensing theory is proposed in this paper.The micro-Doppler parameter estimation algorithm was improved for micro-motion targets with translation in this paper.Relatively ideal micro-Doppler parameter estimation results were obtained.The proposed micro-Doppler parameter estimation was compared with the traditional micro-Doppler parameter estimation algorithm.Requirements for return signal length were analyzed with this new algorithm and its performance was also analyzed in various environments with different SNR.

Micro-Doppler effect testing technique for attitude of projectile in space flight

To measure projectile attitude in space flight, based on continuous wave （CW） radar, a new micro-Doppler effect testing technique is developed in this paper. It also establishes radar testing model for attitude of flying projectile and resolve micro-Doppler effect of projectile motion attitude. By distinguishing and geting attitude parameters such as micro-motion period, this technique can in- tuitively estimate the flight stability of projectile, and the validity of this technique is proved accord- ing to flight tests.

改进M-D结构的二次多变量Hash算法

针对传统Hash算法有安全缺陷的问题,利用有限域上多变量二次方程组求解(MQ)问题的困难性,设计了一种新的基于有限域上多变量二次多项式的Hash算法.新算法给出了一个改进的M-D结构,采用了NMAC(nested MAC)的思想,并加入了计数器,旨在抵抗一些针对传统M-D结构的攻击.新算法具有可调的输出参数,可以适应不同程度的安全性需求.新算法可以抵抗常见的攻击,且具有良好的雪崩效应.新算法相对于以往的多变量Hash算法,在内存需求上和运行速度上都有一定的优势.

Banach空间中m-d增生映射零点的强弱收敛定理

本文研究了m-d增生映射的零点以及有限个m-d增生映射公共零点的迭代设计问题.利用Lyapunov泛函与广义f投影映射等技巧,在Banach空间中,证明了迭代序列强收敛或弱收敛到m-d增生映射的零点或有限个m-d增生映射的公共零点.与以往的相关研究工作相比,迭代设计中考虑了误差项、迭代格式被简化、限定条件被削弱.

A^2/O前置M-D地埋式一体化生物反应器处理某小城镇综合污水

以浑河上游某支流河污水处理工程为实例,介绍A2/O前置M-D地埋式一体化生物反应器处理综合生活污水工艺的设计参数、处理效果及工程投资和运行成本。该项工程处理水量为500t/d,进水BOD5、COD和SS、NH3-N、TN、TP的质量浓度分别为138mg/L、305mg/L和150、35、33、4mg/L。运行结果表明,对BOD5、COD、SS、NH3-N、TN和TP的去除率分别为88.4%、86.9%、93.3%、82.9%、63.6%和75%,比传统A2/O工艺具有更好的脱氮除磷效果。出水水质达到GB 18918-2002的一级B要求,处理费用1.18元/t。该工艺具有运行成本低、高效快速、操作管理方便等突出优点。

FORMULA OF GLOBAL SMOOTH SOLUTION FOR NON-HOMOGENEOUS M-D CONSERVATION LAW WITH UNBOUNDED INITIAL VALUE

In this article, we prove the existence and obtain the expression of its solution formula of global smooth solution for non-homogeneous multi-dimensional（m-D） conservation law with unbounded initial value; our methods are new and essentially different with the situation of bounded initial value.

关于M-D及相关不等式

本文利用控制不等式理论给出了Mitrinovic-Djokovic不等式的一个控制证明和相关不等式,建立了若干新的不等式.

新性价比之选 技嘉B150M-D3H主板

随着新一代100系列主板的更新,作为上代性价比之选的B85平台也迎来了它的继任者——B150。相较于上一代主板平台,B150的变化主要体现在四方面:CPU插槽由LGA1150变为LGA1151;DMI 2.0总线全面升级至DMI 3.0;支持DDR3/4两种规格的内存;原生支持1个SATA-Express接口。今天笔者向大家推荐的便是技嘉B150M-D3H主板,这款主板在国美在线的售价仅为569元,比其他电商低100元左右,十分超值,近期有装机需求的小伙伴可以考虑入手。

入门超频小板 技嘉Z97M-D3H

20周年纪念版奔腾G3258唤起了广大DIY玩家对超频沉寂已久的热情。入门级Z97超频主板也开始在市场上活跃起来。技嘉Z97M-D3H是一款定位入门级超频的m ATX紧凑型小板,MOSFET和南桥芯片上覆盖的黄色散热片给沉稳的黑色PCB带来了一些活泼的气息。CPU供电部分,技嘉Z97M-D3H采用了成熟的4相供电设计,搭配以全固态电容,支持超耐久4PLUS标准。

一块主板全都有 技嘉GA-J1900M-D3P评测

整合主板在追求性能的DIY玩家眼中不值一提,但是高清玩家们却非常钟爱它们。随着硬件的不断发展,性能的不断增强,整合主板在高清硬解性能、多接口输出和低功耗的表现上更加抢眼。今天为大家介绍的技嘉GA-J1900M-D3P不但小巧精致,同时还板载了Intel Bay Trail-D赛扬J1900四核心处理器,连处理器都一并奉送,那么到底这块主板表现怎么样呢,我们一起来看看。

Two-Dimensional Riemann Problems:Transonic Shock Waves and Free Boundary Problems

We are concerned with global solutions of multidimensional(M-D)Riemann problems for nonlinear hyperbolic systems of conservation laws,focusing on their global configurations and structures.We present some recent developments in the rigorous analysis of two-dimensional(2-D)Riemann problems involving transonic shock waves through several prototypes of hyperbolic systems of conservation laws and discuss some further M-D Riemann problems and related problems for nonlinear partial differential equations.In particular,we present four different 2-D Riemann problems through these prototypes of hyperbolic systems and show how these Riemann problems can be reformulated/solved as free boundary problems with transonic shock waves as free boundaries for the corresponding nonlinear conservation laws of mixed elliptic-hyperbolic type and related nonlinear partial differential equations.

弹道目标平动补偿与微多普勒特征提取方法

针对传统逆合成孔径雷达(ISAR)成像中的平动补偿方法并不适用于弹道目标平动补偿的问题,该文提出了一种弹道目标平动补偿与微多普勒(m-D)特征提取方法。在分析有翼弹道目标未完成平动补偿时的m-D效应的基础上,首先采用形态学中的骨架提取方法抑制1维距离像旁瓣,再在快时间频率(距离)-慢时间平面上搜索分离各散射点的m-D特征曲线,然后对其进行经验模式分解(EMD)分解,利用分解结果中的趋势项分量完成目标回波的平动补偿,并通过分析EMD分解结果获得了目标的自旋频率、锥旋频率等特征信息。仿真实验验证了所提方法的有效性与鲁棒性。

OFD-LFM MIMO雷达中旋转目标微多普勒效应分析及三维微动特征提取

该文将微多普勒效应引入到多输入多输出(MIMO)雷达技术研究,以旋转运动目标为例,分析了雷达辐射正交频分线性调频信号(OFD-LFM)时目标的微多普勒效应,给出了其参数化表达。在此基础上,进一步将微多普勒理论从目前的雷达视线方向上的微动分量提取扩展到微动部件3维运动和结构特征提取,利用MIMO雷达的多视角特性,提出了构建多元非线性方程组求解旋转部件的3维运动参数的算法,实现了目标3维微动特征的提取。仿真实验验证了算法的有效性和鲁棒性。