Moving target indication

About: Moving target indication is a research topic. Over the lifetime, 2653 publications have been published within this topic receiving 32435 citations.

Heart-beat detection and ranging through a wall using ultra wide band radar

Abstract: Heart-beat detection has found many applications in military and bio-medical areas. Many of these applications focus on the use of impulse based ultra wide band (UWB) radars. This in-turn requires expensive hardware and consumes more power (for a given range) compared to stepped frequency continuous wave (SFCW) radars. However, the micro-Doppler characteristic of human body can be detected by SFCW radar at much lower sampling rates and power. It can help in distinguishing a living and a non-living target. In addition, SFCW radar can help separate Doppler signatures in down-range, thus enabling it to look for multiple human targets. UWB radars operate at a bandwidth higher than 0.5 GHz and have the benefit of high range resolution. This paper focuses on the experimentation of a technique to obtain the range and Doppler of a human body using UWB-SFCW radar and moving target indicator (MTI) filter, in the presence of an interfering wall.

Joint equalization filters that mitigate waveform-diversity modulation of clutter

Abstract: Moving-target indication radars require advanced signal processing to be able to use pulse-to-pulse waveform diversity. The primary challenge is range-sidelobe modulation (RSM) of clutter. Because range sidelobes differ on each pulse, clutter energy that leaks into range sidelobes cannot be cancelled. We find that higher target SINR can be be obtained by joint design of the pulse-compression filters to obtain impulse responses that match across pulses. The proposed filters can reduce RSM by 5–10 dB compared to low-sidelobe mismatch filters designed separately for each pulse.

Preliminary comparison of high range resolution signatures of moving and stationary ground vehicles

Abstract: High-Range Resolution (HRR) radar modes have become increasingly important in the past few years due to the ability to form focused range profiles of moving targets with enhanced target-to-clutter ratios via Doppler filtering and/or clutter cancellation. To date, much research has been performed on using HRR radar profiles of both moving and stationary ground targets for Automatic Target Recognition (ATR) and Feature-Aided Tracking (FAT) applications. However, little work evaluating the correlation between moving versus stationary HRR profiles has been reported. This paper presents analytical comparisons between HRR profiles generated from a moving vehicle and profiles formed from Synthetic Aperture Radar (SAR) images of the identical stationary vehicle. The moving target HRR profiles are formed by integrating range-Doppler target images detected from clutter suppressed phase history data. The stationary target HRR profiles are formed from SAR imagery target chips by segmenting the target from clutter and reversing the image formation process. The purpose of this research is to identify which features, such as profile peaks, peak intensity, electrical length, among others, are common to profiles of the same target type and class and at the same imaging geometry.

Improved GMTI-tracking using road-maps and topographic information

Abstract: Tracking ground targets with airborne GMTI sensor measurements proves to be a challenging task due to high target density, high clutter, and low visibility. The exploitation of non-standard background information such as road maps and terrain information is therefore highly desirable for the enhancement of track quality and track continuity. The present paper presents a Bayesian approach to incorporate such information consistently. It is particularly suited to deal with winding roads and networks of roads. Key issues are: modeling the target dynamics in quasi one-dimensional road coordinates and mapping onto ground coordinates using linear road segments. The case of several, intersecting roads with different characteristics, such as mean curvature, slope, or visibility, is treated within an Interacting Multiple Model scheme. The iterative filter equations are formulated within a framework of Gaussian sum approximations on the one hand and a numerically exact Particle Filter approach on the other hand. Simulation results for single targets taken from a realistic ground scenario show strongly reduced target location errors compared to the case of neglecting road-map information. By using a realistic GMTI sensor model, early detection of stopping targets is demonstrated.© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The Fundamental Trajectory Reconstruction Results of Ground Moving Target From Single-Channel CSAR Geometry

Abstract: Synthetic aperture radar (SAR) ground moving target indication (GMTI) has attracted a lot of interest from researchers for its ability of simultaneously obtaining high-quality images of stationary scenes and detection of moving targets. In recent years, the research on moving target tracking besides detection by using SAR-GMTI has also raised interest. Compared with standard SAR, the long observation time of circular SAR (CSAR) makes it possible for moving target trajectory reconstruction. By using a prior knowledge of the road information, an effective method for moving target trajectory reconstruction in single-channel CSAR is proposed in this paper. First, the radar echo is segmented according to subapertures, and the Doppler filtering is performed on each subaperture echo for clutter suppression. Second, the range walk induced by target motion is compensated by the keystone transform, and trajectories in range–Doppler domain are obtained. Last, the moving target trajectory in ground coordinate is reconstructed by using the dynamic programming algorithm with road information restrain. Experimental SAR data processing results show that the method is effective for the moving target trajectory reconstruction.