Kenneth I. Ranney

Hyperspectral anomaly detection within the signal subspace

This letter describes the extension of signal subspace processing (SSP) to the arena of anomaly detection. In particular, we develop an SSP-based, local anomaly detector that exploits the rich information available in the multiple bands of a hyperspectral (HS) image. This SSP approach is based on signal processing considerations, and its entire formulation reduces to a straightforward (and intuitively pleasing) geometric and algebraic development. We extend the basic SSP concepts to the HS anomaly detection problem, develop an SSP HS anomaly detector, and evaluate this algorithm using multiple HS data files

Automatic through the wall detection of moving targets using low-frequency ultra-wideband radar

This paper presents a time-domain, Moving Target Indication (MTI) processing formulation for detecting slow-moving personnel behind walls. The proposed time-domain MTI processing formulation consists of change detection and automatic target recognition algorithms. We demonstrate the effectiveness of the MTI processing formulation using data collected by an impulse-based, low-frequency, ultra-wideband radar. In this paper, we describe our radar system and algorithms used for the automatic detection of moving personnel. We also analyze the false alarm and detection rate of four operational scenarios of personnel walking inside wood and cinderblock buildings.

Signal subspace change detection in averaged multilook SAR imagery

This paper addresses change detection in averaged multilook synthetic aperture radar (SAR) imagery. Averaged multilook SAR images are preferable to full-aperture SAR reconstructions when the imaging algorithm is approximation-based (e.g., polar format processing) or when motion data are not accurate over a long full aperture. We examine the application of a SAR change-detection method, known as signal subspace processing, which is based on the principles of two-dimensional adaptive filtering, and we use it to recognize the addition of surface landmines to a particular area under surveillance. We describe the change-detection problem as a trinary hypothesis testing problem, and define a change signal and its normalized version to determine whether: 1) there is no change in the imaged scene; 2) a target has entered the imaged scene; or 3) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are presented for averaged noncoherent multilook and coherent single-look X-band SAR imagery.

Through-the-wall detection of slow-moving personnel

This paper presents a time-domain, Moving-Target-Indication (MTI) processing formulation for detecting slow-moving personnel behind walls. The proposed time-domain MTI processing formulation consists of change detection and tracking algorithms. We demonstrate the effectiveness of the MTI processing formulation using data collected by the Army Research Laboratorys (ARLs), Ultra-Wideband (UWB), Synchronous Impulse Reconstruction (SIRE) radar. During the collection of the data, the SIRE radar remains stationary and is positioned broadside to the wall and 38 degrees off the broadside position. We have collected data for multiple operational scenarios including: personnel walking inside wood and cinderblock structures, personnel walking in linear and non-linear trajectories, and multiple personnel walking within the building structure. We analyze the characteristics of moving target signatures for the multiple operational scenarios and describe the detection and tracking algorithms implemented to exploit them.

Recent MTI experiments using ARL's synchronous impulse reconstruction (SIRE) radar

The Army Research Laboratory (ARL) has recently developed the ground-based synchronous impulse reconstruction (SIRE) radar - a low-frequency radar capable of exploiting both a real antenna array and along-track integration techniques to increase the quality of processed imagery. We have already demonstrated the systems utility by imaging static scenes. In this paper we address the moving target indication (MTI) problem, and we demonstrate the impulse-based systems ability to both detect and locate slowly moving targets. We begin by briefly describing the SIRE system itself as well as the system configuration utilized in collecting the MTI data. Next we discuss the signal processing techniques employed to create the final MTI image. Finally, we present processed imagery illustrating the utility of the proposed method.

Passive sensing for adaptable radar bandwidth

A spectrum sharing technique is introduced that passively monitors the RF spectrum for sub-bands of high signal to interference plus noise ratios (SINR) within a constrained bandwidth of interest. The goal of the proposed technique is to allow the radar to maintain high levels of SINR within selected frequency sub-bands in a highly congested RF environment. A sub-band is selected for radar that maximizes SINR and minimizes the range resolution cell size, two conflicting objectives. In this paper, a spectrum sensing experiment is conducted to collect multiple frequency spectra that are processed by the proposed technique. It will be shown that the proposed technique identifies frequency sub-bands of high SINR while maintaining range resolution requirements.

Noncoherent Approach for Through-the-Wall Moving Target Indication

A moving target indication, noncoherent change detection algorithm is introduced to detect moving targets inside buildings. The proposed algorithm is designed to attenuate image artifacts observed in coherent change detection images by utilizing noncoherent change detection, a positive threshold operation, and sidelobe minimization. The proposed algorithm is compared with coherent change detection for three moving target scenarios. It is shown that the proposed algorithm significantly reduces imaging artifacts while preserving the moving target signature.

Moving target indication with non-linear radar

A new approach for detecting a particular class of moving targets is presented. This method exploits characteristics of specific non-linear targets to both eliminate moving objects that are not of interest and suppress stationary clutter. Details of the underlying physical phenomena are discussed, and the signal processing procedures leveraged by the non-linear radar system are outlined in detail.

Adaptive change detection in coherent and noncoherent SAR imagery

This paper is concerned with change detection in averaged multi-look SAR imagery. Averaged multi-look SAR images are preferable to full aperture SAR reconstructions when the imaging algorithm is approximation based (e.g., polar format processing), or motion data are not accurate over a long full aperture. We study the application of a SAR change detection method, known as signal subspace processing, that is based on the principles of 2D adaptive filtering (M. Soumekh, January 1999) and we use it to recognize the addition of surface landmines to a particular area under surveillance. We identify the change detection problem as a trinary hypotheses testing problem, and identify a change signal and its normalized version to determine whether there is i) no change in the imaged scene; ii) a target has entered the imaged scene; or iii) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are provided with a realistic X band SAR platform using averaged noncoherent multi-look and coherent single-look SAR imagery.

Modified difference change detector for small targets in SAR imagery

One of the most straightforward techniques for detecting changes in an image involves forming the difference between a test image and a reference image. Unfortunately, such a technique can give rise to a large number of false alarms due to the statistical variability of the underlying pixel values, as has been well established within the radar community over the years. One method for dealing with this large number of false alarms involves forming the ratio, rather than the difference, of two synthetic aperture radar (SAR) images. We introduce a modified version of the standard differencing technique to overcome problems associated with pixel value variability. The new (modified) differencing approach utilizes assumptions about the statistics of the image background and the object being sought (target) to reduce the number of false alarms due to highly variable background (clutter) regions, and it includes the standard ratio test as a special case. In fact, we find that the modified difference approach can also be viewed as a modified version of the ratio test with a threshold that varies as a function of the background clutter radar cross section (RCS). We also present an abridged, albeit suboptimal, version of this approach that eliminates assumptions regarding the targets probability distribution, and we analyze both of the approaches. We then compare these results with those obtained with a standard ratio test, and illustrate how the modified difference test reduces to the ratio test under certain operating conditions. The abridged version of the modified approach is applied to high resolution synthetic aperture radar imagery and compared with results obtained with the classical differencing technique, and following this, the modified difference technique is compared with the standard ratio test. Results suggest that under appropriate conditions the abridged, modified technique can successfully detect changes without the need for any image segmentation.