Filtering of moving targets using SBIR sequential frames

In this paper three-dimensional (3-D) finite-impulse response (FIR) filters are proposed for moving target detection and tracking from multiframe space-based infrared (SBIR) data. An optimal, in the l_p sense, 3-D FIR filter design technique is proposed which is suitable for the above application. This technique is the first 3-D FIR design of its kind presented in the open literature. Directional, matched, and adaptive 3-D filtering techniques are proposed. Prior to the filtering, clutter mean estimation and mean subtraction are required. Real time implementation of directional and/or matched filters for processing maneuvering targets is discussed and filter design methods are proposed. Finally, performance comparisons of the proposed and other available 3-D FIR and infinite-impulse response (IIR) filters, on real SBIR data, are presented in which the advantages of the proposed 3-D filters are shown     

利用FIR滤波器生成随机振动试验驱动信号的新方法

 阐述了一种利用有限冲击响应(FIR) 滤波器生成随机振动试验驱动信号的新方法。该方法通过设计一个FIR 滤波器对白噪声序列进行滤波,使滤波器输出序列的功率谱密度满足试验驱动信号的要求。在随机振动试验控制中,将FIR 滤波器和试验的受控对象组成增广系统,这将有助于简化对控制系统的分析和设计。     

A new algorithm to optimize Barker code sidelobe suppressionfilters

The authors suggest a new algorithm for binary coding waveform sidelobe reduction after matched filtering and present a general method by which optimized sidelobe suppression filters for Barker codes can be obtained with a peak output sidelobe 2.62 dB lower than the results found in the literature (for 13-b Barker code). This optimization algorithm is also promising for other binary coding waveforms, such as truncated pseudonoise (PN) sequences and concatenated codes. This new approach can readily be applied to sidelobe-reduction filter design for other binary coding waveforms, such as truncated PN sequences, concatenated codes, etc., which often find their applications in radar systems and spread spectrum communication systems     

宽带认知雷达低峰均比波形快速设计算法

发射波形设计是宽带认知雷达系统的关键技术。为了提高宽带认知雷达系统对距离扩展目标的检测性能,建立了目标检测模型,分析了系统的检测性能,在此基础之上研究了基于最大输出信干噪比(SINR)的低峰均比(PAR)波形设计算法。通过将原波形优化问题等效为接收权值与低峰均比波形的联合优化问题,同时利用循环优化的思想,提出了一种低峰均比波形快速设计算法。相比于现有的梯度法以及凸优化算法,该算法所设计的恒模波形信干噪比与二者相当,但算法实现难度明显变小,计算复杂度明显降低。仿真结果证实了算法的有效性。     

On Increasing Usable MTI Filter Bandwidth by Removing Linear-Phase Constraint

It has been shown in the literature that the linear-phase constraint of finite-duration impulse-response (FIR) digital filters can, under certain circumstances, be effectively traded either for a better filter amplitude response or a reduction in the number of filter coeficients. It is shown that such a tradeoff can be exploited for moving target indicator (MTI) radar signal processors to increase the usable bandwidth for target detection. Although it is demonstrated that the increase is significant for narrowband (ground) clutter, it is negligible for wideband (weather) clutter.     

航空发动机转子参数遥测中的FIR编解码器设计

航空发动机转子参数遥测中, 多路并行红外无线数据传输需要多个高速红外编解码器.利用(CPLD)复杂可编程逻辑器件能够同时在单个器件上实现多个编解码器, 有利于减少遥测系统的器件数量, 便于在发动机转子上安装.本文采用CPLD器件设计高速红外编解码器, 以4PPM编码进行了4Mbps的红外数据传输试验, 通过对红外收发器性能和CPLD输入时钟精度的分析, 找出了4PPM编码时数据传输出现差错的原因, 并对编码方式进行了改进设计, 提出2/3PPM和4/5PPM编码方式, 实现了数据的正确传输, 还提高了编码效率和数据传输速率.      

航空发动机双重传感器故障诊断逻辑研究

针对航空发动机控制系统的双重传感器故障,提出了一种采用双路容错设计的卡尔曼滤波器故障检测隔离系统.故障检测隔离系统由一系列卡尔曼滤波器组成,每个滤波器都假定2路传感器故障,而以故障支路外的测量值作为输入量.当双重传感器故障发生时,只有不包含故障传感器信息的滤波器保持较低的估计残差,其他滤波器都会产生较大的估计残差,如此双重传感器故障便可以被隔离.利用滤波器组估计残差的特征,进一步设计合理的运算逻辑,系统就可以同时对传感器单一故障进行检测和隔离.为了验证故障诊断系统的有效性,在发动机慢车状态分别对传感器发生双重故障和单一故障的情况进行仿真.仿真结果表明:故障诊断系统能够准确有效地对传感器双重故障和单一故障进行检测和隔离.      

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

Detection and range/Doppler estimation for colocated sensors

The problem of multisensor detection and high resolution signal state estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques is addressed. The model-based fusion approach offers the potential for increased target resolution in range/Doppler/azimuth space. The approach employs joint detection/estimation filters (JDEF) for target detection and localization. The JDEF approach segments the aggregate nonlinear model over the entire target resolution space into a number of localized nonlinear models by partitioning the resolution space into a number of resolution subcells. This partitioning leads to extremely accurate state estimation. The proposed JDEF approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, decentralized, and distributed data fusion.     

Precise navigation using adaptive FIR filtering and time domainspectral estimation

This paper introduces a new low cost, short range, positioning system based on adaptive finite impulse response (FIR) filtering and time domain spectral estimation. The system can determine absolute positions with a high degree of accuracy and is well suited for real time navigation. The approach is based upon signal processing techniques and a priori knowledge of the system transfer function. The first step is to measure the phase response of the linear transfer function and then using a FIR filter the time response of the system can be determined. The FIR filter computes the time response by performing a deconvolution between the measured phase response, and the complex conjugate of the transfer function. By correlating the known input impulse response with the output of the FIR filter, an error term is generated. The time delay of the system is determined by adjusting the FIR filter coefficients to minimize the error term. Simulated analysis of the system indicates a worst case error of ±16 cm     

Radar Waveform Selection-A Simplified Approach

Radar measurement and resolution performance, as well as target detection in clutter, depend largely on the transmitted waveform. This explains the sizable effort that has gone into studies of radar waveforms, including attempts at the synthesis of optimum waveforms. This paper shows that, despite the unlimited variety of radar signals, waveform selection is a straightforward process. There are only four classes of waveforms, each with distinct resolution properties. When the target environment is analyzed for a particular application, it is rather evident which of these classes will fit the situation best. Choice of the specific waveform within the selected class then is merely a matter of practical implementation. Although the facts used in developing the unified theory of this paper are not new, it is demonstrated that these facts can be combined into an extremely simple theory of waveform design. Much of today's work is guided by past approaches to a particular problem, and when a design is completed there may be a question as to how close to the optimum it is. The theory presented here permits a systematic approach to waveform selection, with the important benefit that the designer knows exactly where and how much he may have deviated from the best design, and why this was done.     

Survey of High-Power Microwave Filters

A summary of research and development work on high-power microwave filters is given here: first, design considerations in high-power microwave filters?power handling capacity, waveform distortion, multimode suppression, and stop and pass band characteristics; second, a discussion of filtering devices and techniques in two broad categories-dominant mode filters and harmonic filters (discussion covers methods of operation and significant characteristics of each filter developed to date); and third, a discussion of applications and limitations of filters in various systems and interference situations. Also included are the availability, cost, size, weight, etc. as functions of frequency for the various filter types.     

A unified approach to the design of decentralized detection systems

A unified approach to the design of decentralized detection networks with arbitrary topologies is proposed and analyzed. In this approach, a decentralized detection system of arbitrary topology is represented by a communication matrix that specifies the interconnection structure of the detection network. This matrix is used to derive the general decision rule using the person-by-person-optimal (PBPO) solution methodology. It is shown that the PBPO decision rule is a likelihood ratio test for statistically independent observations. The threshold of the test is shown to be a function of the decision input vector of the detector under consideration. This unified approach is used to obtain the PBPO decision rules of decentralized detection systems with various topologies. Various results in the literature are verified. In addition, the PBPO decision rules for a decentralized detection system with peer communication are presented. Numerical examples are presented for illustration     

Robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels

The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective- ness of the orooosed aooroach.     

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed Orthogonal-Frequency-Division Multiplexing (OFDM) Multiple-Input Multiple-Output (MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design (AWD) based on a constrained Multi-Objective Optimization (MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.     

Modeling and Performance Evaluation of Nonlinear Satellite Links-A Volterra Series Approach

An analytical solution to the problem of modeling bandpass nonlinear channels and evaluating the performance of digital communication systems operating on them is presented. A method based on a Volterra series representation of the overall channel is first proposed, which allows one to extend to nonlinearities with memory the well-known concepts of complex envelope of bandpass signals and low-pass equivalent of bandpass linear systems. The general results previously mentioned are then applied to digital satellite communication systems operating over nonlinear channels. The effect of a nonlinear amplifier located in the satellite is considered, in combination with that of transmitting and receiving filters located in the Earth stations. In addition, both uplink and downlink noise are taken into account. Basic advantages of this approach are the generality it offers to the analysis and the fact that it allows accurate evaluation of the error probability in a short computer time.     

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking (MTT). To balance the tracking accuracy and real-time performance, the existing Random Finite Set (RFS) based filters are generally difficult to handle the above problems simultaneously, such as the Track-Oriented marginal Multi-Bernoulli/Poisson (TOMB/P) and Measurement-Oriented marginal Multi-Bernoulli/Poisson (MOMB/P) filters. Based on the Arithmetic Average (AA) fusion rule, this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli (PMB) filter, which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence. In order to fuse the different PMB distributions, the Bernoulli components in different Multi-Bernoulli (MB) distributions are associated with each other by Kullback-Leibler Divergence (KLD) minimization. Moreover, an adaptive AA fusion rule is designed on the basis of the exponential fusion weights, which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT. Finally, by comparing with the TOMB/P and MOMB/P filters, the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.     

变频调速系统共模电流分析及其检测方法

变频调速系统中的复杂波形共模电流会影响传统电磁互感器的输出精度及线性度,导致测量结果存在较大误差。针对此问题,首先对系统共模电流的形成机理、流通路径与幅频特性进行分析;然后提出一种结构简单、宽测量范围的磁调制电流互感器,对互感器的检测原理进行了详细说明;最后进行了样机设计和试验验证。结果表明,所提出的磁调制互感器能够有效测量不同幅频特征的复杂波形电流信号,满足变频调速系统共模电流的测量要求。     

一种基于波形的距离扩展目标检测方法

针对高分辨率雷达距离扩展目标检测问题,提出了一种基于一维距离像波形的距离扩展目标检测器。分析了目标一维距离像的波形特点,对一维距离像的离散序列进行FFT变换,获得变换后的低频分量平均值与高频分量平均值的比值,以其中最大的比值作为检测统计量并进行有无目标的判决。仿真结果表明,此检测方法的检测性能要优于依赖于散射中心空间分布密度的广义似然比（SSD—GLRT,Spatial Scattering Density—Generalized Likelihood Ratio Test）检测器,并且明显优于基于波形熵的检测器。     

功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势，可以更加充分地利用频谱资源。设计了一种新的一体化波形，在实现通信符号传递的同时，利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出，其中以星座图上的范数误差衡量通信性能，以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际，在问题求解时同时考虑了波形总功率约束和波形恒模约束，并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。