Detection Performance of the Cell Averaging LOG/CFAR Receiver

The cell averaging LOG/CFAR receiver is a special implementation of a constant-false-alarm-rate (CFAR) receiver in which the noise level estimate is derived from a set of contiguous time samples of the output of a logarithmic (LOG) detector as obtained from a tapped delay line. This CFAR receiver is capable of operating over a larger dynamic range of noise levels than a conventional cell averaging CFAR receiver, but with somewhat poorer detectability. The performance in stationary Gaussian noise of the cell averaging LOG/CFAR receiver with no post-detection integration is determined in this paper. For a small number of reference noise samples, results were obtained by a Monte Carlo simulation using the technique of importance sampling. For a large number of reference noise samples, a second moment analysis gave the desired results. Both these results can be summarized in the following simple formula, NLOG = 1.65NLIN - 0.65, which relates the number of reference samples required by each of the two receivers for equivalent performance. Thus, for the cell averaging LOG/CFAR receiver to give the same detection performance as the conventional cell averaging CFAR receiver, the number of reference noise samples has to be increased by up to 65 percent.     

On optimal track-to-track fusion

Track-to-track fusion is an important part in multisensor fusion. Much research has been done in this area. Chong et al. (1979, 1986, 1990) among others, presented an optimal fusion formula under an arbitrary communication pattern. This formula is optimal when the underlying systems are deterministic, i.e., the process noise is zero, or when full-rate communication (two sensors exchange information each time they receive new measurements) is employed. However, in practice, the process noise is not negligible due to target maneuvering and sensors typically communicate infrequently to save communication bandwidth. In such situations, the measurements from two sensors are not conditionally (given the previous target state) independent due to the common process noise from the underlying system, and the fusion formula becomes an approximate one. This dependence phenomena was also observed by Bar-Shalom (1981) where a formula was derived to compute the cross-covariance of two track estimates obtained by different sensors. Based on this results a fusion formula was subsequently derived (1986) to combine the local estimates which took into account the dependency between the two estimates. Unfortunately, the Bayesian derivation made an assumption that is not met. This work points out the implicit approximation made and shows that the result turns out to be optimal only in the ML (maximum likelihood) sense. A performance evaluation technique is then proposed to study the performance of various track-to-track fusion techniques. The results provide performance bounds of different techniques under various operating conditions which can be used in designing a fusion system.     

An Adaptive Threshold System for Nonstationary Noise Backgrounds

The problem of detecting target signals in an ocean environment using active sonar is complicated by the nonstationary background which usually consists of both ambient ocean noise and reverberation. on. In this paper a signal processing system capable of detecting a signal in nonstationary noise is introduced. This system makes use of the mean and variance time functions of the nonstationary noise background in order to design estimation filters which will cope with the nonstationarity. Appropriate statistics of the noise and signal (tone burst) plus noise have been obtained and are used to determine the probabilities of false alarm and detection and the receiver operating characteristics.     

Kirchhoff方法在旋翼前飞噪声预测中的应用研究

将CFD(计算流体力学)技术与噪声预测的Kirchhoff方法相结合,发展了前飞状态下直升机旋翼远场气动噪声的定量预测方法,得到了旋翼噪声的时域解。先用具有解析解的“点源”流动代替旋翼流动,通过比较计算值与理论值,验证了该预测方法的可行性和可靠性;尔后针对AH—1／OLS旋翼模型的两种前飞状态进行计算,通过比较计算值与实验值,进一步验证了本文方法及其所发展的程序的正确性。     

Generalized input-estimation technique for tracking maneuveringtargets

A new input estimation technique for target tracking problem is proposed. Conventional input estimation techniques assume that the target maneuver level is constant within the detection window, which has been the major drawback of the techniques. The proposed technique is developed to overcome this drawback by modeling the target maneuver as a linear combination of some basic time functions. The resulting algorithm has a generalized formulation including earlier works on input estimation. A detection performance of the proposed algorithm is analyzed by investigating the detection sensitivity according to the selection of maneuver models and other design parameters such as the detection window size, measurement noise level, and sampling step size. A computer simulation study shows that the estimation performance of the proposed algorithm is comparable to Bogler's input estimation method while the computation time is greatly reduced     

MEMS冗余惯组小幅值故障检测的PCA算法设计和优化

当组成冗余惯组的陀螺为MEMS陀螺,而故障又为幅值比较小的阶跃故障时(仿真发现,阶跃故障幅值为陀螺噪声方差的10倍左右大小时),使用以往的PCA故障检验方法,陀螺噪声会造成故障检测的困难.针对这种情况,提出了MEMS冗余惯组小幅值故障检测的PCA(Principal Component Analysis)算法设计和优化的方法,在以往PCA算法的基础上结合假设检验算法,考虑了陀螺噪声的影响,降低了MEMS陀螺噪声对故障检测的影响.通过仿真验证,证实了本文算法比以往PCA算法具有更高的检测准确性和灵敏度,这对于提高整个系统的可靠性具有重要意义.     

大型客机起飞着陆过程噪声辐射特性对比分析

 基于准稳态假设和分布点声源模型,并采用最新发展的噪声源半经验参数预测公式,发展和完善了用于飞机飞行过程中噪声辐射预测的计算模型和方法。该计算方法能够预测飞机起飞、着陆过程中的适航噪声,并能够对飞机不同噪声源的噪声辐射特性（声级、频谱特性和指向性等）进行计算分析。以某大型客机为对象,对飞机进场着陆过程和起飞过程中飞机噪声源进行了计算分析,计算结果表明,飞机进场着陆和起飞过程中,不同噪声源对远场噪声级的影响有明显的差异,起飞过程中发动机风扇噪声源是最主要的噪声辐射源,而在进场着陆过程中飞机机体噪声（包括起落架和襟翼等）是重要的飞机噪声源。文中也给出了不同噪声源频谱特性和指向特性等。     

Detection of a Distributed Target

The influence of increasing range resolution on the detectability of targets with dimensions greater than the resolution cell is studied. An N-cell target model is assumed, which contains k reflecting cells, each reflecting independently according to the same Rayleigh amplitude distribution. It will be referred to as the (N,k) target. Detection based on one transmitted pulse is performed against a background of white normal noise. Detection in stationary clutter is also considered. The optimum detector is obtained but, in view of its complexity, the performance of a simpler detector, the square-law envelope detector with linear integrator (SLEDLI), is analyzed, and a formula for the probability of detection is obtained. Graphs are presented which show the probability of detection as a function of signal-to-noise ratio (SNR) for various values of N k, and false alarm probability. For N/k not too large it is shown that the SLEDLI is near optimum.     

Detection Performance of a Mean-Level Threshold

The problem of detecting signals in nonstationary clutter is met by presenting a mean-level or adaptive threshold which adjusts to the changing background level. Such a threshold performs better than a fixed threshold that must be set for the highest amplitude clutter. However, the mean-level threshold does not perform as well for stationary noise as a fixed threshold set at the proper value. One measure of effectiveness of an adaptive threshold is its performance in stationary noise (compared to the optimum fixed threshold) for a specified speed of response. For the mean-level threshold, a simple mathematical solution is found for the detection probability when the noise is stationary and the signal scintillates rapidly. The performance is evaluated for a wide range of mean-level-threshold time constants and for several false-alarm probabilities. The results are presented graphically. As an example, the mean-level threshold suffers 3 dB in detectability (equivalent signal-to-noise ratio) in the presence of stationary noise as compared to the optimum fixed threshold for 50-percent probability of detection, false-alarm probability of 10-8, and an adjustment time of 15 times the signal duration.     

基于切片熵权的WHT多LFM信号识别方法

为提高在低信噪比与先验信息不足条件下对线性调频(LFM)信号识别能力,借鉴信息论中的熵权法改进WHT(Wigner-Hough Transform),提出了一种基于切片熵权的WHTE(Wigner-Hough Transform based on Entropy)算法。推导出LFM信号的WHT与对应特性,将WHT变换域内极半径和角度切片的熵值来转换为权重因子,进而对每个切片进行加权处理,采用双层权重以弱化噪声与干扰项的影响,并推导出LFM信号与高斯白噪声在WHT维度内不同假设条件下的概率密度分布函数,构建了对于LFM信号WHT后恒虚警检测的完备流程。通过理论分析与公式推导论证了算法的可行性,并与WHT、分数阶傅里叶变换与周期WHT算法的仿真对比,验证了算法的有效性,凸显WHTE算法能够在强噪声背景下与没有先验支撑时实现对LFM信号的良好检测。     

Doppler visibility of coherent ultrawideband random noise radar systems

Random noise radar has recently been used in a variety of imaging and surveillance applications. These systems can be made phase coherent using the technique of heterodyne correlation. Phase coherence has been exploited to measure Doppler and thereby the velocity of moving targets. The Doppler visibility, i.e., the ability to extract Doppler information over the inherent clutter spectra, is constrained by system parameters, especially the phase noise generated by microwave components. Our paper proposes a new phase noise model for the heterodyne mixer as applicable for ultrawideband (UWB) random noise radar and for the local oscillator in the time domain. The Doppler spectra are simulated by including phase noise contamination effects and compared with our previous experimental results. A genetic algorithm (GA) optimization routine is applied to synthesize the effects of a variety of parameter combinations to derive a suitable empirical formula for estimating the Doppler visibility in dB. According to the phase noise analysis and the simulation results, the Doppler visibility of UWB random noise radar depends primarily on the following parameters: 1) the local oscillator (LO) drive level of the receiver heterodyne mixer, 2) the saturation current in the receiver heterodyne mixer, 3) the bandwidth of the transmit noise source, and 4) the target velocity. Other parameters such as the carrier frequency of the receiver LO and the loaded quality factor of the LO have a small effect over the range of applicability of the model and are therefore neglected in the model formulation. The Doppler visibility curves generated from this formula match the simulation results very well over the applicable parameter range within 1 dB. Our model may therefore be used to quickly estimate the Doppler visibility of random UWB noise radars for trade-off analysis     

一种变信噪比条件下的恒虚警野值检测方法

野值检测又称异常值检测,是模式识别、机器智能和知识发现等领域经常面临的一个问题。当出现环境失配,数据信噪比（SNR）发生变化时,测试样本和训练样本所含噪声会有不同方差,以往的野值检测方法在虚警控制方面将会失效。针对这一问题,提出一种基于归一化残差（NR）的野值检测方法。该方法首先根据所需虚警概率和噪声方差变化情况确定野值检测门限,其次基于训练样本计算待考查模式的NR值,再比较NR值与检测门限的相对大小,从而判断待考查模式是否为野值。这一方法所依赖的检测门限对所需虚警率和噪声方差变化具有适应能力,因此可以在变信噪比条件下实现恒虚警（CFAR）野值检测。仿真实验验证了所提方法在虚警控制和野值检测方面的优越性能。     

Comments on "Optimum Bandwidth of a Low-Pass Filter for Detection of a Pulse in Nonstationary Noise"

In a recent correspondence1 a calculation of the optimum bandwidth of a low-pass RC filter for the detection of a pulse signal in nonstationary noise was presented. The purpose of this correspondence is: 1) to point out additional references to the work which has been conducted in the stationary noise case, and 2) to present an interesting alternate derivation of the expected output noise power for the nonstationary noise case.     

基于喇曼散射的分布式光纤测温系统光接收机灵敏度的分析

在分布式光纤测温系统中,携有温度信息的喇曼散射光是极其微弱的,只有 n W量级,而温度变化引起的喇曼散射光的变化更加微弱。在对光接收机噪声分析的基础上,给出了该类应用条件下光接收机信噪比。指出了低信噪比下,AD的量化误差将随累加次数的增加而减小,同时 AD的有效位数将增加,给出了低信噪比下 AD有效位数的分析方法,并通过 MATLAB进行了验证,在此基础上,分析了光接收机的灵敏度,由此可以直接计算分布式光纤测温系统的测温精度。     

直升机旋翼厚度噪声研究

噪声设计已成为现代直升机设计的重点。本文从理论上推导了Farassat1A公式,建立了可进行预估直升机旋翼厚度噪声的方法,并对1/4的UH-1直升机旋翼模型和某型机进行了理论计算,研究了桨叶桨尖马赫数、桨叶翼型相对厚度等因素对厚度噪声的影响。     

Envelope Threshold Detection in a Class of Non-Gaussian Interference

This paper considers the detection of a sinusoidal or chirp signal imbedded in wideband FM interference (as might be generated by some types of active jamming), such that after pulse compression or other integration, the interference can be approximated by a sum of sinusoids of independent phase. The detection probability in such non-Gaussian noise is compared to that for Gaussian noise, with the Gaussian result approached, as required, in the limit that the number of sinusoids in the sum increases without bound. For detection using a comparison of the envelope with a threshold which yields a given false-alarm probability (CFAR detection), the detection probability is improved over the case of Gaussian noise, so that the usual approach basing the design on Gaussian noise would be conservative. Using a threshold determined from the envelope mean, the FM interference yields a lower false-alarm probability than for Gaussian noise, with detection probability only slightly degraded.     

Probability Density of the Click Duration in an Ideal FM Discriminator

The expression of the probability density function PClick(T) of the duration r of the clicks is determined as a function of 1) the expected number of clicks per second, Felick 2) the expected number of times per second that the noise component x(t) in phase with the carrier has instantaneous amplitude larger than that of the carrier itself 3) the probability density function peross(T) of the duration of the time intervals in which x(t) < -A 4) the probability that the values of the noise component in quadrature with the carrier will be of opposite sign at the extremes of time intervals of duration v. Using for Pcross(T) an approximate formula that holds fairly well in the range of the values of the signal-to-noise power ratio ? usually encountered, PIick(T) has been calculated for several values of a and for two shapes of the noise spectrum, Gaussian and rectangular. Finally, an expression is given for the mean value of T.     

非线性非高斯模型的高斯和PHD滤波算法(英文)

A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density （GSPHD） filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaussian sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival probability, and detection probability are all Gaussian sums. The analysis also shows that the existing Gaussian mixture probability hypothesis density （GMPHD） filter, which is unsuitable for handling the non-Gaussian noise cases, is no more than a special case of the proposed algorithm, which fills the shortage of incapability of treating non-Gaussian noise. The multi-target tracking simulation results verify the effectiveness of the proposed GSPHD.     

基于高灵敏超导探测器的新型脉冲光高精度光纤陀螺技术研究

高精度光纤陀螺的精度主要由光纤陀螺检测噪声决定,一般可用角随机游走系数来表征,光纤陀螺的角随机游走主要由光路干涉信号的信噪比和信号处理引入的噪声决定。提出了基于高灵敏超导探测器的脉冲光高精度光纤陀螺技术方案和精度提升方法,实现了陀螺光信号的高灵敏检测,显著降低了光纤陀螺的热噪声,降低了相对强度噪声,并避免了连续光因调制切换引入的尖峰脉冲误差的影响,有效提升了光纤陀螺的精度水平。通过仿真分析,可将光纤陀螺的随机游走系数检测极限从3.53×10-5(°)/h1/2降低至1.6×10-5(°)/h1/2,减小了约54.7%。     

Acquisition Time of Tracking Loops Operating in the Frequency-Search Mode

This paper presents a theory for computing the signal acquisition time of a second-order tracing system operating in the frequency-search mode. In particular, a closed-form expression is obtained which relates the acquisition time to the relevant system parameters, to the initial loop detuning, and to the slope of the ramp that sweeps the voltage-controlled oscillator. Although the theory is only approximate and the resulting formula is exact only in the limit when the initial loop detuning ?F goes to infinity, it has been found that it gives quite accurate results as soon as ?F is some times greater than the equivalent noise bandwidth of the loop.