SPTM-2.1

A Computationally-Efficient Two-Step Implementation of the GLRT Detector
Nicholas B Pulsone, Michael A Zatman (M.I.T. Lincoln Laboratory)

In this paper, a new two-step implementation of the GLRT is proposed. A disadvantage of the GLRT detector is that it is more computationally complex than the simple AMF detector. Our two-step implementation of the GLRT significantly reduces the computational load with a negligible loss in detection performance.

SPTM-2.2

Coherent Detection of Radar Signals in G-Distributed Clutter
George Mamic, Nathan Stitt (School of Electrical & Electronic Systems Eng. Queensland University of Technology), Robert Iskander (Communications and Information Processing Group, School of Electrical & Electronic Systems Eng. Queensland University of Technology)

Recently the G distribution has been proposed as a new model for extremely heterogeneous clutter in SAR returns. In this paper, we develop a technique for estimating the parameters of the G~distribution, show that the G distribution represents an amplitude distribution of a spherically invariant random process for certain values of its parameters, and design coherent detectors for known and unknown signals embedded in G-distributed clutter. The performance of the detectors under specific conditions is then provided.

SPTM-2.3

Direct Joint Source Localization and Propagation Speed Estimation
Chris W. Reed, Ralph Hudson, Kung Yao (UCLA)

This paper describes two new techniques for the joint estimation of source location and propagation speed using measured time difference of arrival (TDOA) for a sensor array. Previous methods for source location either assumed the array consisted of widely separated subarrays, or used an iterative procedure that required a good initial estimate. The first method directly estimates the source location and propagation speed by converting the solution of a system of nonlinear equations to an overdetermined system of linear equations with two supplemental variables. The second method provides improved estimates by using the solution of the first method as initial condition for further iteration. The Cramer-Rao Bound (CRB) on the joint estimation is derived, and simulations show the new methods compare favorably to the bound.

SPTM-2.4

Source Detection and Localization Using a Multi-Mode Detector: A Bayesian Approach
Douglas Cochran, Dana Sinno, Axel Clausen (Arizona State University)

This paper considers a class of detection/localization problems in which the detector offers multiple operating modes. The modes differ in their detection performance and geographical coverage: "focused" modes offer higher detection performance but less coverage area than "broad search" modes. It is assumed that a signal source is to be detected and localized using a sequence of tests, each possibly employing a different mode. The goal is to determine a strategy for mode selection in the sequence of tests that will yield optimal payoff in terms of a pre-established criterion. A mathematical model capturing the key characteristics of this situation is proposed and used to develop optimal mode selection strategies.

SPTM-2.5

Asymptotic Non-Null Distribution of the Generalized Coherence Estimate
Axel Clausen, Douglas Cochran (Arizona State University)

The use of the generalized coherence estimate as a statistic for detection of a common signal in multiple independent channels of additive gaussian noise has been studied in several recent papers. This work has relied on simulations to evaluate detector performance because the distribution of the generalized coherence estimate with signal present is unknown. This paper derives an asymptotic expression for the non-null distribution of the estimate as the length of the sample sequences approaches infinity, develops an asymptotic performance analysis based on this distribution, and compares the receiver operating characteristics derived from this theoretical approach to those obtained using simulations with large sample sequence lengths.

SPTM-2.6

New Methods of Radar Detection Performances Analysis
Jean-Philippe Ovarlez (ONERA DEMR/TSI), Emmanuelle Jay (ONERA DEMR/TSI and ENSEA/UCP-ETIS)

Original methods of radar detection performances analysis are derived for a fluctuating or non-fluctuating target embedded in additive and a priori unknown noise. This kind of noise can be, for example, the sea or ground clutter encountered in surface-sited radar for the detection of target illuminated at low grazing angles or in high resolution radar. For these cases, the spiky clutter tends to have a statistic which strongly differs from the gaussian assumption. Therefore, the detection theory becomes difficult to perform since the nature of statistics has to be known. The new methods proposed here are based on the parametric modelisation of the moment generating function of the noise envelope by Pad� approximation and lead to a powerful estimation of its probability density function. They allow to evaluate the radar detection performances of target embedded in any noise without knowledge of the closed form of its statistic and allow in the same way to take into account any possible fluctuation of the target. These methods have been tested successfully on synthetic signals and have been performed on experimental signals such as ground clutter.

SPTM-2.7

An Undecimated Wavelet Transform Based Detector for Transients in 1/f Noise
Thomas T Liu, Antony C Fraser-Smith (Space, Telecommunications and Radioscience Laboratory, Stanford University, Stanford, CA 94305)

We consider the detection in the presence of 1/f noise of a known transient signal of unknown amplitude, scale and delay. We introduce a generalized likelihood ratio test (GLRT) method based on pattern matching in the undecimated discrete wavelet transform (UDWT) domain. In many cases, the computational complexity of the detector can be reduced with minimal performance impact by limiting the pattern matching operations to locations in the UDWT domain that correspond to the existence of transform local maxima. As examples of our approach, we simulate the detection of transients that are modeled either by scaling functions, Gaussian functions, or two-sided exponential functions.

SPTM-2.8

Detecting multipath signals with the matched-lag filter
John L Spiesberger (Pennsylvania State University)

A detection problem is considered for a single broadband source of unknown waveform and emission time. The signal travels to the receiver along multipath with unknown delays and temporal separation exceeding the inverse bandwidth of the signal. The received noise has uncertain variance. The travel times of the multipath are impractical to predict because of uncertainties in the environment. The presence or absence of the signal is estimated from the auto-correlation function. Instead of stochastically modeling the multipath in terms of their received auto-correlation function, receivers are constructed which constrain the signal-related lags in the auto-correlation function to have physically possible arrangements. For simple cases, this approach, called a matched-lag filter, yields probabilities of detection that are 1.35 times greater (for a false-alarm probability of 0.001) than conventional filters which base their decision on the signal-to-noise ratio in the auto-correlation function.

SPTM-2.9

Performance of the Optimal Nonlinear Detector/Tracker in Clutter
Marcelo G Bruno, Jose M Moura (ECE Department, Carnegie Mellon University)

We propose in this paper an optimal nonlinear Bayesian algorithm for joint detection and tracking of targets that move randomly in cluttered environments. We review the derivation of the optimal Bayesian detector/tracker and present Monte Carlo simulations that benchmark the detection and tracking performances in both spatially correlated and non-Gaussian clutter.

SPTM-2.10

Robust Signal Detection Using the Bootstrap
Hwa-Tung Ong, Abdelhak M Zoubir (Cooperative Research Centre for Satellite Systems)

This paper presents a CFAR detector based on the bootstrap for detecting signals with unknown amplitude, phase and frequency such as found in conventional pulsed radar and sonar systems. The detector is robust against non-Gaussian noise, and can still maintain the false alarm rate without much modification if consistent estimates are substituted for unknown parameters. Preliminary asymptotic results are given on the performance of the detector, and simulations are used to study the performance for small samples sizes.

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Last Update: February 4, 1999 Ingo Höntsch