A method for improving extended Kalman filter performance forangle-only passive ranging

A relatively simple method is presented which eliminates previously reported (Oct. 1985) erratic estimation performance associated with Cartesian formulations of the extended Kalman filter (EKF) for the 2D angle-only emitter location problem. The technique is based on an initialization procedure which combines a priori probability density function (pdf) information with single measurement a posteriori pdf information in a manner which is more efficient than the EKF. Simulation results are presented which demonstrate the utility of the technique as compared with a previously offered modified gain EKF     

Principal components, covariance matrix tapers, and the subspaceleakage problem

A new class of robust space-time adaptive beamforming techniques is introduced to address a broad range of subspace leakage phenomena that arise in many sensor array applications. When present, these leakage phenomena can significantly increase the effective rank of the dominant colored noise interference spectrum, thereby reducing the appeal of techniques that exploit low-rank dominant interference (such as principal components (PC) or diagonal loading) to reduce sample support (training) requirements. By combining the covariance matrix taper (CMT) approach with either PC or diagonal loading, the minimal sample support properties of these techniques can be preserved     

Improved clutter mitigation performance using knowledge-aided space-time adaptive processing

This paper presents a framework for incorporating knowledge sources directly in the space-time beamformer of airborne adaptive radars. The algorithm derivation follows the usual linearly-constrained minimum-variance (LCMV) space-time beamformer with additional constraints based on a model of the clutter covariance matrix that is computed using available knowledge about the operating environment. This technique has the desirable property of reducing sample support requirements by "blending" the information contained in the observed radar data and the a priori knowledge sources. Applications of the technique to both full degree of freedom (DoF) and reduced DoF beamformer algorithms are considered. The performance of the knowledge-aided beam forming techniques are demonstrated using high-fidelity simulated X-band radar data     

Knowledge-aided signal processing: a new paradigm for radar and other advanced sensors

Recently, significant progress has been made in the development of physics-based, knowledge-aided (KA) signal processing strategies supported by improvements in real-time embedded computing architectures. These developments provide designers of advanced sensor systems an unprecedented degree of flexibility when implementing next generation adaptive sensor systems. In the case of radar, this has been manifested in the first ever, real-time, KA space-time adaptive processing (KA-STAP) system for advanced clutter/interference suppression. This paper provides exemplars of real-world effects giving rise to the need for "intelligent" adaptation schemes and overviews the KA approach to sensor signal processing in some detail. Moreover, we survey a collection of papers describing recent KA sensor research that follow in this issue     

Performance bounds for hot and cold clutter mitigation

A new method is presented for describing the theoretical interference space-time covariance matrix that will be observed in an adaptive airborne radar system under specific topographical conditions. Both hot clutter that is induced by interfering sources and cold clutter that results from the radar transmitter are considered. This method incorporates phenomenology observed under site specific conditions as well as system effects such as array geometry, receiver filtering, and system bandwidth. Use of this formulation rather than sample data analyses that are generally employed enables one to infer performance bounds for site-specific, and thus generally, heterogeneous terrain that are tighter and therefore more meaningful than the thermal noise floor limit     

Full-polarization matched-illumination for target detection and identification

This paper investigates the optimization of the full-polarization radar transmission waveform and the receiver response to maximize either target detection or identification performance. Application of such full-polarization matched-illumination techniques to simulated VHF-band frequency response data of mobile surface targets yields a significant performance improvement over that corresponding to chirped full-polarization transmission waveforms.