Long CPI Wideband GMTI
Abstract
The conventional approach to GMTI uses narrowband signals and a short coherent processing interval (CPI). In this talk, we examine some of the fundamental theoretical issues involved in GMTI with wideband signals and long CPIs (WL-GMTI). The possibility of wideband long CPI GMTI has received some attention in recent years and there are a number of potential benefits: 1) Improved minimum detectable velocity (MDV). 2) Detection of targets with zero radial velocity (but non-zero tangential velocity. 3) Better fit with dual-use SAR/GMTI architectures. 4) Less demanding array requirements (shorter and/or sparser arrays). 5) Greater robustness to clutter internal motion. The most convenient framework for WL-GMTI is a post-SAR architecture where each spatial channel is pre-processed with synthetic aperture radar (SAR) image processing. The post-SAR architecture is the natural generalization of post-Doppler STAP to the wideband long-CPI case. Exact steering vectors in the post-SAR framework are computed analytically for constant-velocity targets assuming a calibrated array. The steering vectors can be used with algorithms such as the GLRT or AMF to perform adaptive detection on the post-SAR data. We also derive a simple exact expression for SINR loss when the covariance is known exactly. The loss is a two-dimensional function of both target velocity components indicating the capability to detect both radial and non-radial target motion. The final section of this talk examines WL-GMTI performance bounds based on optimal Bayesian detection. In particular we study how detection performance varies as a function of the number of pixels that the moving target "smears" over in the SAR image. There is a surprising improvement in detection performance when the clutter has strong non-Gaussian tails. In at least some cases, it appears that much of the performance can be achieved with a simple sub-optimal detector.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 20, 2004
- Accession Number
- ADA432617
Entities
People
- Ali Yegulalp
Organizations
- Massachusetts Institute of Technology