Space and time filter separates slow target
from ground clutter
STAP Processing Chain
Data Cube ABSTRACT
In this paper, we first present the principles of STAP and discuss the properties of optimum detector, as well as problems associated with estimating the adaptive weights such as ambiguities and the high computational cost. The performances are evaluated highlighting the influence of radar parameters on the detection of slow targets. To resolve problem of high computational cost of optimal STAP, reduced-rank methods are used. And to resolve Doppler ambiguities, staggering of PRF is used. The simulation results are presented and the performances of STAP are discussed. In addition, the effect of an interfering target is analyzed. The performances of detection are discussed using two parameters: power and direction of the interfering target. Numerical evaluation is based on two models of staggering PRF: quadratic and pseudo- random, with two methods for reducing rank: Principal Components and SINR metric.
It was shown that the primary target is completely masked if the interfering target is powerful and this for any direction of the second target. It was also proven as when this one is located according to particular directions of the jammers, detection is largely degraded. To cure these problems, one considered an analysis of the staggered PRF of the STAP with the two methods which showed their effectiveness.The simulated environment is a linear side looking network of N antennas spaced out by d and M impulses in the CPI. The elevation angle is fixed to 20°. The speed of the airborne radar is VR=100m/s, and the frequency of transmission is 0.3GHz. The environment of the interferences is composed of:
- (i) Five jammers whose angles of azimuth are: 0°, 180°, 60°, 90°et, 72°, with jammer reports/ratios on noise (JNRs) of 13dB, 12dB, 11dB, 10dB, and 9dB respectively.
- (ii) Clutter of ground covering the band [- 30°, 30°], and of clutter to noise ratio (CNR) equal to 8 dB.
In addition to the above assumptions, the environment of the interferences is composed of an interfering target whose power and direction are the parameters of analysis. The performance of detection will be discussed in the case of a scenario without ambiguities, PRF 8VR / , for better seeing the effect of the interfering target. This does not prevent us from mentioning the case of a scenario with ambiguities. All the simulations were carried out over 20 Monte Carlo runs
Previously, same authors in: Digital Information Processing and Communications
Communications in Computer and Information Science
Volume 189,
2011,
pp 244-257
Two-Dimensional Signal Adaptive Processing for Airborne Radar
Two-Dimensional Signal Adaptive Processing for Airborne Radar - Springer
In static radars, all the ground returns are received with a Doppler frequency almost null. However, in airborne radars, they present a wide spectrum for the Doppler frequencies because of the platform in motion. Space-time adaptive processing (STAP) was introduced to improve the capacity of radars to detect slow moving targets which can be masked by clutter or jammer. In this paper, we present the principles of STAP and we discuss the properties of optimum detector, as well as problems associated with estimating the adaptive weights such as ambiguities and the high computational cost. The performances are evaluated highlighting the influence of radar parameters on the detection of slow targets. To resolve problem of high computational cost of optimal space-time processing, reduced-rank methods are used. And to resolve Doppler ambiguities staggering of PRF is used. The simulation results are presented and the performances of STAP are discussed.
STAP use in VADER and in Dual Beam Lynx
spendergast: Northrop Grumman to Operate VADER Man-Hunting Radar for UAV in AfghanistanGA-ASI First Two-Channel Lynx Radar Demonstrates Improved GMTI Performance Under Darpa Dual Beam Project
If jammers are non-stationary (in the statistical sense) and the clutter is non-stationary (in the same sense), then two of the three components of the covariance that are needed to apply STAP successfully are missing. A random process having time varying 2nd order statistics causes non-stationarity. From 1st principles of random processes, if random process (or time series) is non-stationary, then it is not ergotic and the covariance apparently cannot be calculated from ensemble averages of time record on-line (in real time or in post processing). Too bad!
ReplyDeleteSee Kerr, T. H., “Vulnerability of Recent GPS Adaptive Antenna Processing (and all STAP/SLC) to Statistically Non-Stationary Jammer Threats,” Proceedings of SPIE, Session 4473: Tracking Small Targets, pp. 62-73, San Diego, CA, 29 Jul.-3 Aug. 2001.
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STAP only works for wide band stationary White Gaussian Noise jammers. There are at least 21 other jamming or spoofing approaches in existence. Wht don't DOD and ARINC acknowledge this fact? Rose colored glasses?