On detection using filter banks and higher order statistics

We suggest a method, based on the use of filter bank and higher order statistics (cumulants), for detection of transient signals. The method first uses a bandpass filter bank, which separates the spectrum of the observed signal into narrow frequency bands. Each subfilter of the filter bank is then followed by a cumulant estimator, and thereby suppressing colored noise. By selecting those subfilters that have large output energies, the filter bank can approximate the behavior of a matched filter. Moreover, no a priori information about the waveform of the signal is needed. The performance of the detector is evaluated by using a simulated signal as well as a measured signal. The presented detector is compared with the optimal matched filter detector.     

Some Matched Filter Configurations for Infrared Systems

An analysis of the output of three alternative matched filter configurations in an infrared scanning system model is presented. The sensor is corrupted by thermal noise, generation-recombination noise, photon noise, and modulation noise, the latter providing an extreme discoloration in the signal passband. Expressions for the signal voltage density spectrum, signal pulse shape, noise power spectrum, and average noise power at the matched filter output are derived where the integral evaluations attendant to these derivations do not appear elsewhere in the literature. The paper also provides graphical displays of the signal-to-noise power ratio at the filter output versus various system parameters, noise power spectrum out of the matched filter versus ?, and the signal pulse shape out of the filter versus time. Also included are discussions of practically realizable approximations to the matched filters and curve fitting techniques for the signal pulse shape function.     

口径近场的特征谱

 提出口径近场特征谱的概念,以描述口径设计近场特征。特征谱包括角域谱和时域谱,分别定义为口径近场区空域场和频域场在角域和时域的变换。理论分析和计算结果表明,特征谱可以在角域和时域上分离有限大口径的直达波和绕射波,因而可以用来描述口面尺寸、形状和场分布等条件改变时绕射场的相对变化,这对紧缩场设计具有参考价值。基于口面场卷积法,计算、比较了限度为5 m×5 m圆口径和方口径近场在X波段特征谱分布。并导出：口径近场角谱为口径场角谱和网络响应函数角谱的乘积,网络响应函数等效于一个空间角谱滤波器。     

一种全自动的检测方法用于SAR-ATI的GMTI

针对星载SAR-ATI处理的中间结果,提出了一种称为"两步-类高斯拟合"完全自适应的检测方法。该方法可以完全自动地实现杂波和噪声中的运动目标检测,避免了传统方法作联合高斯数据的假定,无须推导SAR-ATI干涉图的理论概率密度函数。此外,该方法还可以大大降低系统的虚警概率并用仿真研究了最小可检测速度。     

基于液晶光阀的动态红外场景仿真研究

介绍了基于液晶光阀的动态红外场景仿真系统构成,分析了液晶光阀的波长变换和空间调制机理。对反映红外场景仿真效果主要因素(光谱输出特性、时间响应特性和空间分辨力)进行了理论分析和研究。利用优化设计液晶光阀参数构建的动态红外场景仿真样机,测量其光谱输出特性、时间响应特性和空间分辨力,结果表明,仿真系统的输出光谱可覆盖中波和长波红外波段,可实现帧频70Hz,系统空间分辨力优于10 lp/mm(受红外光学系统和红外热像仪分辨力限制)。     

Angular Accuracy of a Scanning Radar Employing a Two-Pole Filter

A two-pole filter is proposed as a detector for a scanning radar. The optimum values of the filter coefficients are found and are approximated by a simple expression. The optimum two-pole filter requires a 0.15-dB increase in signal-to-noise ratio in order to provide the same detection capability as the optimum detector, and yields azimuth estimates whose standard deviation are within 15 percent of the Cramér-Rao lower bound. The estimator is simple to implement, avoiding the storage requirements of the moving window detector and the bias complications of the feedback integrator.     

Logarithmic Detection with Postdetection Filtering

An analysis is presented of the performance of a logarithmic detector or followed by a low-pass filter, under the assumption of a large ratio of IF bandwidth to postdetection bandwidth. This allows for the probability of detection and similar quantities to be computed in a straightforward manner. The mean and variance of the filter output are found by first deriving the autocorrelation function of the logarithmic detector output and then obtaining the power spectral ral density. A useful engineering approximation is made for the variance which is valid for all signal-to-noise ratios.     

Detection of Known Signals in Nonstationary Noise

The basic design of a nonlinear, time-invariant filter is postulated for detecting signal pulses of known shape imbedded in nonstationary noise. The noise is a sample function of a Gaussian random process whose statistics are approximately constant during the length of a signal pulse. The parameters of the filter are optimized to maximize the output signal-to-noise ratio (SNR). The resulting nonlinear filter has the interesting property of approximating the performance of an adaptive filter in that it weights each frequency band of each input pulse by a factor that depends on the instantaneous noise power spectrum present at that time. The SNR at the output of the nonlinear filter is compared to that at the output of a matched filter. The relative performance of the nonlinear system is good when the signal pulses have large time-bandwidth products and the instantaneous noise power spectrum is colored in the signal pass band.     

A Kalman Filter Based Tracking Scheme with Input Estimation

Beginning with the derivation of a least squares estimator that yields an estimate of the acceleration input vector, this paper first develops a detector for sensing target maneuvers and then develops the combination of the estimator, detector, and a "simple" Kalman filter to form a tracker for maneuvering targets. Finally, some simulation results are presented. A relationship between the actual residuals, assuming target maneuvers, and the theoretical residuals of the "simple" Kalman filter that assumes no maneuvers, is first formulated. The estimator then computes a constant acceleration input vector that best fits that relationship. The result is a least squares estimator of the input vector which can be used to update the "simple" Kalman filter. Since typical targets spend considerable periods of time in the constant course and speed mode, a detector is used to guard against automatic updating of the "simple" Kalman filter. A maneuver is declared, and updating performed, only if the norm of the estimated input vector exceeds a threshold. The tracking sclheme is easy to implement and its capability is illustrated in three tracking examples.     

Mean Power Estimation with a Recursive Filter

Power estimates from smoothed detector outputs of stationary signals are analyzed for linear, square law, and logarithmic receiverdetectors. Smoothing is accomplished with a first-order recursive digital filter. lnput amplitude is assumed to be Rayleigh distributed and detector output samples independent. Expansion of results to other distributions is indicated.     

A mean level adaptive detector using nonconcurrent data

Convergence results for a mean level adaptive detector (MLAD) are presented. The MLAD consists of an adaptive matched filter (for spatially correlated inputs) followed by a mean level detector (MLD). The optimal weights of the adaptive matched filter are estimated from one batch of data and applied to a statistically independent batch of nonconcurrent data. The threshold of the MLD is determined from the resultant data. Thereafter a candidate cell is compared against this threshold. Probabilities of false alarm and detection are derived as a function of the threshold factor, the order of the matched filter, the number of independent samples per channel used to calculate the adaptive matched filter weights, the number of samples used to set the MLD threshold, and the output signal-to-noise power ratio of the optimal matched filter. A number of performance curves are shown and discussed     

Energy Detection of a Random Process in Colored Gaussian Noise

A likelihood receiver for a Gaussian random signal process in colored Gaussian noise is realized with a quadratic form of a finite-duration sample of the input process. Such a receiver may be called a "filtered energy detector." The output statistic is compared with a threshold and if the threshold is exceeded, a signal is said to be present. False alarm and detection probabilities may be estimated if tabulated distributions can be fitted to the actual distributions of the test statistic which are unknown. Gamma distributions were fitted to the conditional probability densities of the output statistic by equating means and variances, formulas for which are derived assuming a large observation interval. A numerical example is given for the case in which the noise and signal processes have spectral densities of the same shape or are flat. The optimum filter turns out to be a band-limited noise whitener. The factors governing false alarm and detection probabilities are the filter bandwidth, the sample duration, and the signal level compared to the noise. Two sets of receiver operating characteristic curves are presented to complete the example.     

Planck-LFI 44 GHz back end module

This work describes the principle of operation, assembly and performance of one branch of the 44 GHz back end module (BEM) for the Planck low frequency instrument (LFI). This subsystem constitutes a fully representative branch of the qualification-model version (QM). It includes waveguide to microstrip transition, GaAs pseudomorphic high electron mobility transistor (PHEMT) low noise amplifiers (LNA), bandpass filter, square-law detector and dc amplifier. The fundamentals of the design of the RF part are described and all of the components have been tested individually before integration. Using single tone and wideband noise stimuli, the output voltage has been measured for several input powers, in order to obtain the sensitivity factor of the complete BEM. The effective bandwidth and the equivalent noise temperature have been calculated from the measurements, taking into account the frequency dependence on the noise source and the BEM. Finally, the low frequency output power spectrum has been obtained and a maximum 1/f knee frequency around 200 Hz has been measured with a 3 dB output signal video bandwidth above 50 KHz.     

A Comparison of Complementary and Kalman Filtering

A technique used in the flight control industry for estimation when combining measurements is the complementary filter. This filter is usually designed without any reference to Wiener or Kalman filters, although it is related to them. This paper, which is mainly tutorial, reviews complementary filtering and shows its relationship to Kalman and Wiener filtering.     

Spectral Analysis of Optimal and Suboptimal Gyro Monitoring Filters

Gyro monitoring filters are used to estimate and correct gyro drift rates of local-level inertial navigation systems. Conventional gyro monitoring filters are usually designed based on a simplified model of gyro drift rate. Furthermore, the effectiveness of these filters-and of many filters of the "Kalman" type-is often measured in terms of the root mean square (rms) criterion in contrast to the spectral content criterion typical of classical Wiener filtering theory. This paper has two objectives: to propose a gyro monitoring filter which is based on a more detailed model of gyro drift rate; and to propose a method of filter performance evaluation which uses as criterion a measure of the spectral content of the error process. The proposed gyro monitoring filter is shown to have improved spectral contents resulting in superior navigation performance for the gyro error models used in the calculations (comparable to commercial-grade aircraft gyros).     

Detection by incoherent recombination with partial information

Matched filter (MF) detection in spread environments is often seriously degraded by the mismatch between the waveform replica and the composite signal formed by the spreading environment. Typically the spreading is caused by multiple delayed reflections due to scatter extent or multipath especially in shallow water sonar applications. It is possible to recover some detector performance by incoherent summation of weighted MF realizations in a process called incoherent recombining (IR). Several IR strategies for Gaussian data that assume varying amounts of prior scattering function (SF) information are examined, their receiver operating characteristics (ROCs) computed, and compared with those of the unrealizable “prescient” receiver (PR). They include optimally weighted and unweighted versions of the maximum likelihood estimator-correlator (EC), and variations of the “at-least-one” (ALO) detector that examines sequences of MF realizations declaring a detection if at least one threshold is crossed. As might be expected, performance improves with the accuracy of the prior information incorporated in the detector formulation     

Absorption of high energy gamma-rays by low energy intergalactic photons

Following our previously proposed technique, we have used the recent -ray observations of Mkr421 to place theoretically significant constraints on the magnitude of the intergalactic infrared radiation field (IIRF). Our 2 upper limits are consistent with normal IR production by stars and dust in galaxies. They rule out exotic mechanisms proposed to produce a larger IIRF. Although they are still subject to revision and are unconfirmed, the data on the spectrum of Mkr421 hint at a possible absorption cutoff which could be produced by an IIRF of the magnitude expected from stellar emission and reprocessing in galaxies. Using models for the low energy intergalactic photon spectrum from microwave to ultraviolet energies, we calculate the opacity of intergalactic space to -rays as a function of energy and redshift. These calculations indicate that the GeV -ray burst recently observed by the CGRO EGRET detector originates at a redshift less than 1.5.     

Modified Generalized Sign Test Processor for 2-D Radar

The modified generalized sign test processor is a nonparametric, adaptive detector for 2-D search radars. The detector ranks a sample under test with its neighboring samples and integrates (on a pulse-to-pulse basis) the ranks with a two-pole filter. A target is declared when the integrated output exceeds two thresholds. The first threshold is fixed and yields a 10-6 probability of false alarm when the neighboring samples are independent and identically distributed. The second threshold is adaptive and maintains a low false-alarm rate when the integrated neighboring samples are correlated and when there are nonhomogeneities, such as extraneous targets, in the neighboring cells. Using Monte Carlo techniques, probability of false-alarm results, probability of detection curves, and angular accuracy curves have been generated for this detector. The detector was built and PPI photographs are used to indicate the detector's performance when the radar is operated over land clutter.     

防空导弹攻击目标的红外成像特性分析

通过结合对目标的红外成像特性研究,首先阐述了在复杂背景条件下防空导弹对目标的红外成像寻的制导的组成和原理。然后详细分析了地面杂散背景的辐射和散射特征,综合分析了军用飞机被防空导弹攻击目标的红外辐射特性。在对复杂背景辐射特征和目标红外特性分析的基础上,给出了一组典型地表光谱辐射亮度曲线和太阳对地表的全波段辐射能流(辐照度)随时间的变化曲线;绘制出了红外成像导引头在整个红外波段内的探测效能曲线。分析结果对研究防空导弹红外成像导引头如何从复杂背景中将目标的典型特征信息提取出来并进行有效识别和跟踪奠定了基础。     

Performance Degradation of MTI Circuits Due to Amplitude Limiting

The loss in output signal-to-noise ratio (SNR) due to amplitude limiting is obtained for a radar circuit consisting of a bandpass limiter, coherent demodulator, matched filter, and moving-target-indicator (MTI) filter. The circuit is used in scanning MTI radars. The tandem connection of the limiter and coherent demodulator is a model for the saturation of the intermediate-frequency (IF) demodulator of an MTI radar. Results on special functions are used to obtain simple formulas for the loss in output SNR relative to a linear IF demodulator when the input SNR is less than -15 dB and the number of hits per 3-dB beamwidth exceeds 15.