通道参数对MIMO雷达估计性能的影响效果分析

为在目标参数估计中正确处理MIMO雷达收发通道网的未知系数,提出并建立了3种通道参数模型,分别推导了各模型下的目标估计和克拉美罗界(Cramer-Rao lower bound,CRLB),比较了各模型下的参数估计性能,研究了通道参数的不同处理方法对MIMO雷达估计性能的影响效果。理论分析表明,在目标估计时如果将通道系数作为未知参量与目标参数联合估计,可比将其作为随机参量求期望获得更高的参数估计精度,而且随着信噪比的降低两者的参数估计性能差异会随之扩大。仿真实验也验证了上述结论的正确性。     

基于相参处理的宽脉冲信号参数估计快速算法

提出了一种宽脉冲信号参数估计快速算法,利用抽取的方法来降低宽脉冲信号参数估计的计算量。首先,对宽脉冲正弦波信号进行抽取构造相参脉冲串,利用相参脉冲频率估计算法进行频率估计。其次,对于宽脉冲线性调频信号,对其做延时相关之后即可转化为宽脉冲正弦波信号,然后在上述抽取和相参处理方法的基础上即可得到宽脉冲线性调频信号参数估计值。性能分析和仿真结果表明,该算法在保证一定的参数估计精度前提下,大大降低了算法的计算量,有利于宽脉冲信号参数估计的实时处理。     

多天线协同接收PSK载波参数估计的CRLB

针对利用多个独立天线对同一信号进行协同接收的问题,推导了数据辅助（DA）和非数据辅助（NDA）方式BPSK/QPSK信号频率及相位估计的Cramer-Rao下界（CRLB）,并与传统单个天线接收时的CRLB进行了比较。结果表明,在DA方式下,多天线协同接收PSK信号频率及相位估计的CRLB与传统单天线接收的CRLB相同;在NDA方式下,多天线协同接收的CRLB则要低于传统单天线接收的CRLB。     

高斯噪声下伪码-线性调频复合信号参数提取方法

针对目前雷达信号参数估计算法在某种环境中性能急剧下降,甚至失效的问题,提出一种基于多相滤波器组和高阶累积量联合处理的伪码-线性调频复合信号参数估计算法.该算法首先利用多相滤波器组实现信号在频域上快速均匀划分,然后对输出的每个子带信号进行三阶累积量对角切片的短时估计,有效抑制高斯噪声的干扰,并经过包络检波后得到复合信号完整的时频矩阵,最后通过时频图像的Radon变换和频率曲线的提取实现信号伪码数目、码元宽度、调频斜率、信号载频、带宽以及起止频率的提取.仿真结果表明,该方法在信噪比大于-11 dB时的估计精度较高.     

连续波背景下多信号处理方法

对接收到的信号进行短时傅里叶变换，通过分析短时傅里叶变换中每一个时间片内的信号频谱，检测出连续波背景下的脉冲信号。滤除线性调频脉冲信号成分，保留连续波信号成分，得到调频连续波信号具有周期性的时频变化曲线。根据连续波信号时频变化曲线的频谱特征，估计出其主要参数，然后滤除脉冲信号出现时间内信号中的连续波成分，并采用相应的方法估计出其参数。仿真结果表明，本文算法可以准确估计出线性调频连续波（LFMCW）信号和线性调频（LFM）脉冲信号的参数，当LFMCW信号的信噪比高于-8dB，并且其功率比脉冲信号功率小6dB以上时，算法具有良好的估计精度和稳定性。     

Coherent integration loss due to pulses loss and phase modulation in passive bistatic radar

The purpose of this paper is to analyze the amplitude and phase modulation effect incurred by the rotating transmit antenna in passive bistatic radar, which result in pulses loss and phase reversals within the direct-path pulse train. The processing loss mechanisms of signal to noise ratio (SNR) and offsets in target Doppler measurements caused by the pulses loss and phase reversals are described. The expressions of the peak output of cross-ambiguity function are derived to evaluate SNR loss in the presence of pulses loss or/and phase reversals. Simulation results show that the maximum SNR loss is about 3.5 dB, and the SNR loss curves for various Doppler frequencies and different number of lost pulses are conformed to the theoretical analysis. The SNR loss gets progressively worse with increasing target Doppler frequency. The frequency estimation error increases with target Doppler frequency and lost pulse number, up to a worst case of about 0.75 of a Doppler cell.     

一种OFDM系统中的符号定时同步方法

正交频分调制（OFDM）是一种高效的数据传输技术,具有良好的抗频率选择性衰落能力,并且提高了频谱利用率。但是OFDM对同步误差十分敏感,特别是符号同步误差。传统的MLE算法虽对符号定时估计很有效,但在ISI干扰情况下性能不高。针对MLE算法的不足,提出了一个基于新的算法。同时通过Matlab的模拟仿真表明,在信噪比较高时,新的算法定时估计性能优于MLE算法。     

基于CS理论的LFM信号DOA估计*

针对常用LFM（linear frequency modulated）信号DOA（direction of arrival）估计算法采样数据量大,在低信噪比情况下估计效果不理想的问题,提出一种基于CS（compressed sensing或compressive sampling）理论的LFM信号DOA估计新方法。实验仿真验证了CS理论的基本原理及运用其进行LFM信号DOA估计的可行性。     

重频参差相参脉冲串频率估计算法

研究了重频参差相参脉冲串的频率估计算法。通过脉内相关积累,提高了新序列的信噪比。对新序列的相位差按参差重数抽样平均,减小了等效的相位噪声方差,利用重频参差比解相位模糊,扩大了频偏允许范围,降低了算法的信噪比门限。分析了本算法实现相参频率估计的条件,推导了相应信噪比门限的解析表达式,指出了信噪比门限与信号样本总数、参差重数、参差比之间的关系。仿真结果表明:上述结论是正确的,在满足信噪比门限条件下,频率估计的精度接近相参脉冲串频率估计的克拉美-罗限(CRLB)。     

Alternative Parameter Estimation Methods for the Compound Poisson Software Reliability Model with Clustered Failure Data

The ‘compound Poisson’ (CP) software reliability model was proposed previously by the first named author for time-between-failure data in terms of CPU seconds, using the ‘maximum likelihood estimation’ (MLE) method to estimate unknown parameters; hence, CPMLE. However, another parameter estimation technique is proposed under ‘nonlinear regression analysis’ (NLR) for the compound Poisson reliability model, giving rise to the name CPNLR. It is observed that the CP model, with different parameter estimation methods, produces equally satisfactory or more favourable results as compared to the Musa–Okumoto (M–O) model, particularly in the event of grouped or clustered (clumped) software failure data. The sampling unit may be a week, day or month within which the failures are clumped, as the error recording facilities dictate in a software testing environment. The proposed CPNLR and CPMLE yield comparatively more favourable results for certain software failure data structures where the frequency distribution of the cluster (clump) size of the software failures per week displays a negative exponential behaviour. Average relative error (ARE), mean squared error (MSE) and average Kolmogorov–Smirnov (K–S Av.D_n) statistics are used as measures of forecast quality for the proposed and competing parameter-estimation techniques in predicting the number of remaining future failures expected to occur until a target stopping time. Comparisons on five different simulated data sets that contain weekly recorded software failures are made to emphasize the advantages and disadvantages of the competing methods by means of the chronological prediction plots around the true target value and zero per cent relative error line. The proposed generalized compound Poisson (MLE and NLR) methods consistently produce more favourable predictions for those software failure data with negative exponential frequency distribution of the failure clump size versus number of weeks. Otherwise, the popularly used competing M–O log-Poisson model is a better fit for those data with a uniform clump size distribution to recognize the log-Poisson effect while the logarithm of the Poisson equation is a constant, hence uniform. The software analyst is urged to perform exploratory data analysis to recognize the nature of the software failure data before favouring a particular reliability estimation method. © 1997 by John Wiley & Sons, Ltd.     

线性调频信号的一种新的频域脉压处理方法

线性调频波形由于多普勒性能突出，一直是一种在雷达中具有广泛应用的脉冲压缩波形，但是线性调频的距离旁瓣不够理想，强目标的旁瓣过高就有可能淹没弱目标的主瓣。该文根据线性调频信号的频谱结构，采用频域数字处理技术，提出了一种新的基于理想压缩脉冲的频域滤波器（SSF）设计方法，导出了可实现低的压缩脉冲距离旁瓣的条件。与其它方法相比，线性凋频信号由该文方法压缩后主副瓣比得到很大的提高，并且主瓣不会展宽，因此不影响距离分辨力。通过数学公式推导和计算机仿真表明，所提出的方法是正确的和可行的，而且步骤简单，运算量小，易于实现。     

相参脉冲信号识别方法和性能分析

提出了一种相参脉冲信号识别算法,通过检测脉冲相位的线性度判别序列的相参性.该算法通过相参积累,有效地提高了信号的信噪比.文中讨论了门限的选取对算法性能的影响,给出了相应的数学推导,并通过仿真实验对推导结果加以验证.同时还讨论了算法的信噪比门限.仿真实验表明,本方法可以在较低信噪比情况下实现对脉冲信号相参性的识别.本文算法有助于实现对脉冲多普勒雷达的识别和告警,对研制数字射频存储器也具有重要意义.     

Frequency division multiplexing technique for composite ambiguity function approximation

In this paper, we propose a frequency division multiplexing (FDM) diversity waveform technique to achieve a delay-Doppler response that approximates the composite ambiguity function (CAF) in a multiple target scenario. First, a channel estimate based on maximum likelihood estimation (MLE) for each subband is provided, and the signal to noise power ratio (SNR) needed to achieve the specific variance requirement of the MLE is derived. Next, using the Doppler transformation, we show how to combine the output response of each subband undergoing a different Doppler shift. Then the CAF approximation of each detected target is derived based on the coherent CLEAN algorithm. Finally, the CAF approximation of all the targets is attained, having the improved delay-Doppler resolution and thus providing a way to resolve initially undetected targets using a recursive procedure.     

基于数据抽取的相参脉冲串载频精确估计方法

利用相参脉冲串信号的相位相干特性,提出一种利用FFT和数据抽取技术的精确测量载频的新方法。该方法利用数毫秒信号,达到了亚kHz量级的频率估计精度和数十Hz量级的频率分辨能力。仿真试验验证了该方法的频率精确测量能力和频率高分辨能力。     

基于部分相关的LFM脉冲全参数估计

针对线性调频（LFM）脉冲信号的侦察问题,提出了调频率、中心频率、信号到达时间、脉宽全套参数集的估计方法。首先,使用分数阶傅里叶变换（FrFT）对信号的调频率与时频关系进行估计;紧接着选取部分相关脉冲对信号进行积累,利用自相关处理完成中心频率、信号到达时间、脉宽参数的估计;然后推导了估计参数的克拉美劳下界（CRLB）,分析了信噪比对估计误差的影响;最后分析了部分积累脉宽对估计误差的影响,给出了积累脉宽的选择范围。仿真分析表明,调频率估计误差几乎达到CRLB,在信噪比0 dB、基带与调制参数均未知的条件下,中心频率估计均方根误差约为10^-1MHz数量级,信号到达时间和脉宽估计均方根误差约在10^-1 μs数量级。参数估计误差受到相关脉冲宽度的影响,随着相关脉冲宽度的增加,估计误差呈现先减小后增大的趋势。所提方法特别适用于脉压、合成孔径等新体制雷达的侦察。     

水平门限同积模型参数的拟极大似然估计

提出了用于非平稳非线性时间序列建模的水平门限同积模型,给出了模型参数的拟极大似然估计,由于对门限参数和同积向量似然函数既不可微也不光滑,不能直接运用传统的极大似然估计．因此首先利用遗传模拟退火算法估计门限参数和同积向量,然后用极大似然估计计算其余的参数,仿真结果表明,拟极大似然估计不受模型维数限制具有有效性和可行性,此外,数值计算结果的比较分析表明遗传模拟退火优于传统的遗传算法、模拟退火和随机搜索等优化算法．     

基于分数阶Fourier变换的多分量LFM信号检测与参数估计

介绍了分数阶Fourier变换的基本原理和基本性质，提出了基于分数阶Fourier变换的多分量LFM信号检测和参数估计方法。为了解决多个LFM分量之间的相互影响问题．特别是强分量掩盖弱分量的问题．本文还提出了一种结合逐次消去思想和分数阶Fourier变换的多分量LFM信号检测和参数估计算法，它可以解决强度相差较大的多分量LFM信号中检测和估计弱LFM分量参数的问题。仿真实验结果证明了该算法的有效性。     

基于大数据分析的移动对象轨迹预测方法

对移动对象的轨迹预测将在移动目标跟踪识别中具有较好的应用价值。移动对象轨迹预测的基础是移动目标运动参量的采集和估计,移动目标的运动参量信息特征规模较大,传统的单分量时间序列分析方法难以实现准确的参量估计和轨迹预测。提出一种基于大数据多传感信息融合跟踪的移动对象轨迹预测算法。首先进行移动目标对象进行轨迹跟踪的控制对象描述和约束参量分析,对轨迹预测的大规模运动参量信息进行信息融合和自正整定性控制,通过大数据分析方法实现对移动对象运动参量的准确估计和检测,由此指导移动对象轨迹的准确预测,提高预测精度。仿真结果表明,采用该算法进行移动对象的运动参量估计和轨迹预测的精度较高,自适应性能较强,稳健性较好,相关的指标性能优于传统方法。     

A new coherent integration method for weak maneuvering target with jerk motion

In radar systems, prolonging the integration time helps to improve the detection and estimation performance of weak target. However, in a long integration time, target's high-order motion is non-ignorable, which causes high-order range migration (RM) and Doppler frequency migration (DFM) problems. The RM and DFM defocus the integration result and lead to detection and estimation performance loss. In this paper, a new coherent integration method is proposed for maneuvering radar target with jerk motion. First, we define a new cross correlation function basing on non-uniformly resampling technique. By using this function, we eliminate the range migration (RM) and Doppler frequency migration (DFM) caused by target's velocity and acceleration. Then, matched filtering process is performed to compensate the phase error caused by target's jerk motion. Finally, the integration is achieved by summing signal data in different range frequency cells and performing a two-dimensional fast Fourier transform (FFT). The proposed method is applicable for low signal-to-noise ratio (SNR) environment. Compared with the GRFT algorithm, the proposed method has a close integration performance and a lower computational complexity. The effectiveness is validated by simulations and real-data processing results.     

Iterative SNR estimation using a priori information

A class iterative signal-to-noise ratio (SNR) estimation algorithm is proposed in this paper. The data samples are governed by a given distribution with a priori. The expectation maximization (EM) algorithm is applied to iteratively maximize the likelihood function so as to realize the SNR estimation. Cramer–Rao bounds (CRB) with different a priori are compared for binary phase shift keying and orthogonal phase shift keying systems, which show the potential of the SNR estimator in turbo-like systems. In high-order modulations, simulation results show that the reduced-complexity iterative method with equal a priori has better performance in middle or high SNR region than the foregone ones. Moreover, the new method with feedback information is the best when its iteration number is 4 and extrinsic information larger than 0.4. These methods are applied in the bit-interleaved coded modulation with iterative decode (BICM-ID) system to validate the effect of the proposed methods.