Some Limiting Forms of an Innovations-Based Discrete-Time Detection Algorithm

The simplicity and breadth of application inherent in a log likelihood ratio (LLR) test based on the use of the innovations representation in discrete-time detection theory are demonstrated.In particular, it is shown that the innovations-based detection algorithm (IBDA) resulting from this theory contains the solutions to several well-known Gaussian detection problems as special cases.     

Threshold Control for Automatic Detection in Radar Systems

In automatic detection in radar systems an estimate of background clutter power is used to set the detection threshold. Usually detection cells surrounding the cell under test for the presence of a target are used to estimate the clutter power. In the research reported herein, the target location is taken to be uncertain and thus returns from a target could corrupt this clutter power estimate. It is shown how the threshold should be varied to compensate for the resulting degradation in detection performance. The threshold control procedure is based on a priori information about target location that could be supplied by the radar's tracking system. In addition, a simple procedure for calculating detection and false alarm probabilities for Swerling II target models is presented.     

An algorithm for detection of moving optical targets

An algorithm is described for detecting moving optical targets against spatially nonstationary Poisson background and noise. The algorithm has applications in optical detection of objects such as meteors, asteroids, and satellites against a stellar background. A maximum-likelihood approach is used which results in reducing interference from stars. It is shown that by choosing a detection threshold to provide a constant false alarm rate, the resulting algorithm is independent of the signal strength of the target. An analysis of this algorithm is presented, showing the probability of detection for several false-alarm rates     

Bayesian Detection of Targets of Unknown Location

In this paper the array detection problem for certain deterministic signals in spatially uncorrelated Gaussian noise is formulated in Bayesian terms and the required likelihood ratios and resulting performance characteristics are obtained. Primary emphasis is on detection of targets of unknown spatial location using a likelihood ratio approach, with the target location treated as a random parameter, rather than an estimator-correlator approach. The tradeoff among array parameters and signal parameters is demonstrated. It is shown that the dominant uncertainty affecting detection performance seems to be that of location when compared with uncertainty on energy and/or phase.     

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。     

Recursive Methods for Computing Detection Probabilities

Recursive methods are drived for computing detection probabilities for general fluctuating targets in Gaussian noise. For the generalized chi-square family of fluctuating targets, very simple and convenient recursive algrithms result. The methods are also extended to cell-averaging CFAR. Although the detection probability is expressed iw: terms of an infinite series, a convenient expression is derived for the resulting error when the series is truncated. Cell-averaging CFAR results are computed for nonfluctuating, Swering case I, and Swerling case II fluctuating targets.     

Detection of Thin Lines using Low-Quality Video from Low-Altitude Aircraft in Urban Settings

A novel thin line detection algorithm for use in low-altitude aerial vehicles is presented. This algorithm is able to detect thin obstacles such as cables, power lines, and wires. The system is intended to be used during urban search and rescue operations, capable of dealing with low-quality images, robust to image clutter, bad weather, and sensor artifacts. The detection process uses motion estimation at the pixel level, combined with edge detection, followed by a windowed Hough transform. The evidence of lines is tracked over time in the resulting parameter spaces using a dynamic line movement model. The algorithm's receiver operating characteristic curve (ROC) is shown, based on a multi-site dataset with 86 videos with 10160 wires spanning in 5576 frames.     

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     

Calculation of Detection Probabilities for Automated Change Detection

A general model is presented for calculating detection and falsealarm probabilities for the automated change detector. The model is then applied to determine PD'PF for the ?target-no target? type change; the resulting PD and PF are compared to the one-channel case.     

Two-Stage CFAR Detectors for Multiple-Range-Bin Radars

Two-stage detectors using generalized sign and four-level conditional statistics for signal detection in multiple-range-bin radars are described. The resulting detectors are of constant false-alarm rate (CFAR). Performances are evaluated and compared with singlestage versions. If the a priori probability of either the no-target case or the target-presence case is large (close to 1), a two-stage test can be designed to have the advantage of reducing the average number of samples required without sacrificing detection probability. With the proper choices of parameters, significant improvement in the efficiency can be achieved. Asymptotic relative efficiency of two-stage detectors with respect to single-stage detectors is derived and some numerical results are evaluated.     

Detecting small moving objects using temporal hypothesis testing

This paper addresses the problem of detecting small, moving, low amplitude objects in image sequences that also contain moving nuisance objects and background noise. We formulate this problem in the context of a hypothesis testing procedure on individual pixel temporal profiles, leading to a computationally efficient statistical test. The technique assumes we have reasonable deterministic and statistical models for the temporal behavior of the background noise, target, and clutter, on a single pixel basis. Based on these models we develop a generalized likelihood ratio test (GLRT) and perfect measurement performance analysis, and present the resulting decision rule. We also propose a parameter estimation technique and compare its performance to the Cramer Rao bound (CRB). We demonstrate the effectiveness of the technique by applying the resulting algorithm to real world infrared (IR) image sequences containing targets of opportunity. The approach could also be applicable to other image sequence processing scenarios, using acquisition systems besides IR imaging, such as detection of small moving objects or structures in a biomedical or biological imaging scenario, or the detection of satellites, meteors or other celestial bodies in night sky imagery acquired using a telescope     

An Alternative Method for Analyzing the Double Threshold Detector

An alternative method for analyzing the performance of a double threshold or M-out-of-N detector is discussed. Detection performance for the suggested method is based on the probability that a return crosses the threshold for the Mth time (a detection is declared) on the kth return or look. It is shown that this formulation has many advantages, as compared with the conventional method of analysis which employs the binomial probability distribution, since the upper limit N is not contained in the resulting probability expressions. It is shown that the probability of detection obtained by the alternate method is the same as that obtained if the detection method were analyzed as a Markov chain with M+1 states. Use of the method results in simple expressions for the mean and variance of the number of looks before detection, provides an alternative way of estimating the probability of a threshold crossing, and leads to computationally simple bounds for the probability of false alarm.     

Optimization of multiframe target detection schemes

We optimize the performance of multiframe target detection (MFTD) schemes under extended Neyman-Pearson (NP) criteria. Beyond the per-track detection performance for a specific target path in conventional MFTD studies, we optimize the overall detection performance which is averaged over all the potential target paths. It is shown that the overall MFTD performance is limited by the mobility of a target and also that optimality of MFTD performance depends on how fully one ran exploit the information about the target dynamics. We assume a single target situation and then present systematic optimization by formulating the MFTD problems as binary composite hypotheses testing problems. The resulting optimal solutions suggest computationally efficient implementation algorithms which are similar to the Viterbi algorithm for trellis search. The optimal performances for some typical types of target dynamics are evaluated via Monte-Carlo simulation     

Radar detection in clutter

Clutter is defined as any unwanted radar return. The presence of clutter in a range/Doppler cell complicates the detection of a target return signal in that cell. In order to quantify the effect of clutter on the probability of detection, we must first specify sets of models suitable for representing the clutter and target. The simplest and most common model for clutter is based on the gamma density. We include two additional models, the NCG and NCGG clutter models for low grazing angles. They are motivated by physical arguments, the latter of which can accommodate the well-known phenomenon of speckle. Using one of these models for clutter together with one of several models for targets, we determine, in a range/Doppler cell, expressions for probabilities of detection of a target in the presence of clutter. It is important to control the probability of false alarms. The presence of clutter in a cell necessitates an increase in the detection threshold setting in order to control false alarms, thus lowering the probability of detection. If the clutter level is unknown, then we need to take measurements of the clutter and use it to adjust the threshold. The more clutter samples we take, the better the estimate of the clutter level and the less is the resulting detection loss. Using the expressions for the probability of detection in clutter, we can quantify the detection loss for a pair of commonly used constant false-alarm rate (CFAR) techniques and investigate how the loss varies with different parameter values, especially with regard to the number of clutter samples taken to estimate the clutter level.     

MSK and Offset QPSK Modulation with Bandlimiting Filters

It is considered by some that minimum shift keying (MSK) is spectrally more efficient than quaternary phase-shift keying/offset quadrature phase-shift keying (QPSK/OQPSK). An analytical method is presented here for determining the detection efficiencies of MSK and QPSK/OQPSK when the constant-envelope signal is passed through a set of filters and when the resulting signal is corrupted by Gaussian noise. The detection efficiency of MSK is compared with that of QPSK/OQPSK when a four-pole Butterworth filter is used as a transmit filter and for two different receive filter functions. When the two-sided 3-dB bandwidth of the transmit filter is between approximately 1.00/T and 1.50/T, it is shown that the detection efficiency of MSK is not substantially different from that of QPSK/OQPSK. For more severe bandlimiting of the signal, the performance of MSK is shown to be inferior to that of QPSK/OQPSK. It is, therefore, concluded that MSK does not have significantly better detection efficiency when the effect of bandlimiting filters is taken into account.     

Radioisotope detection and identification at high speeds using passive sensors

A network of radiation sensors for the protection of a military base against radiological/nuclear threats has been integrated in a testbed. Two key subsystems of this network are the array of sensitive radiation detectors and the subsystem for notifying the operators of radiation events. The alarm/alert notification subsystem automatically issues notifications to the command post in real-time. The resulting reporting to the command post appears to be adequate for non-technical operational personnel. The CONOPS for the protection system relies on the sensitive detection and identification of all radioactive sources well before the transporting vehicles reach the base gates. This is a unique feature of this protection system. Discriminating sodium-iodide detectors, in conjunction with plastic scintillators and neutron detectors comprise a high-performance detection subsystem. The use of various correlation techniques has permitted the demonstration of the detection of source strengths of tens of /spl mu/Ci moving at highway speeds and at several meters separation. A companion algorithm identifies the detected radioisotope when sufficient counts are available.     

Concentration Measurements in a Transient Helium-Air Mixture Utilizing an Electron Beam

In order to determine the available test time in a helium-driven shock tunnel, an interface detection system has been developed to indicate the arrival of helium driver gas at the test section. This is done by exciting the gas at the test section with a high-energy electron beam and spectroscopically analyzing the resulting fluorescence to determine ine the helium concentration. Relative values of helium and air emission intensities are calculated and compared with experimental data from both static and transient gas mixtures.     

Detectors for Multiomial Input

The binary detection problem is considered. Under an arbitrary noise environment, the input sample space can be transformed into a multinomial vector. Based on observations of this vector, the Neyman-Pearson optimal detector is developed for a known signal. When the signal strength is unknown, the likelihood ratio principle is followed to obtain consistent tests which use the Pearson's chisquare statistic. The resulting detectors are compared to others in terms of asymptotic relative efficiency under some actual noise distributions.     

基于双状态卡方故障检测的组合导航系统

故障检验与隔离是利用联邦滤波实现组合导航系统安全可靠运行的关键技术。针对常规残差卡方检验法对于慢变故障检验效果差,以及状态卡方检验受到初值误差、系统噪声和建模误差影响导致子系统被频繁隔离的问题,提出一种改进的SINS/GPS/ADS/DVL组合导航系统故障检验算法。该算法采用2个状态推进器交替地对滤波数据进行重置,避免状态递推器被未检测出来的故障污染。实验结果表明,改进的算法能够有效提高故障检验的灵敏度,增强组合导航系统的可靠性。     

Satellite intercept targeting DSP algorithm design and evaluation

A unified processing approach for the detection and localization of satellites or other exoatmospheric targets is presented. Enhanced filtering and centroid determination algorithms were developed based on real-time implementation constraints, mission conditions including accuracy requirements, and signature structure. The signature structure consisted of target returns, high-frequency random noise, low-frequency structured noise, and contamination sources resulting from debris and cosmic events. Detailed signal processing analyses were performed to verify the required subsample accuracy and the sensitivity to hardware and system constraints. The resultant system design was functionally verified in a real-time breadboard processor