Low complexity anti -jam processing for GPS via multi-stage nested Wiener filter
Abstract
The core contribution of this dissertation is the development of an anti-jam space-time preprocessor based on power minimization and utilizing the multi-stage nested Wiener filter (MSNWF) as a reduced rank adaptive filtering scheme. The advantage of the preprocessor approach is that it allows the incorporation of anti-jam filtering without modification to the GPS receiver. Space-time power minimization preprocessing prior to the GPS correlators offers the capability of canceling more interferers than space-only processing if there is a mixture of narrowband and broadband interferers. Space-time processing also averts an unnecessary spatial null in the direction of a narrowband interferer which may potentially blot out an angular sector of space where a GPS satellite lies. The disadvantage of space-time processing is the large dimensionality of the space-time weight vector. The higher dimensionality translates into a large computational burden and slow convergence. To increase convergence and lower computational complexity, a space-time MSNWF preprocessor is developed. The promising performance of the space-time preprocessor in terms of rank reduction and nulling performance when using the MSNWF is quantified through theoretical analysis and verified through extensive simulations involving mixtures of both wideband and narrowband jammers. In addition to computational complexity reduction, it is important to minimize GPS signal distortion due to temporal preprocessing. Conjugate symmetry is exploited to enhance the smoothness of the space-time preprocessor response as a function of angle and frequency. In addition, exploitation of conjugate symmetry also serves to reduce memory and computational requirements of the MSNWF. A figure of merit called the Space-Time Preprocessor Performance Gain (STPPG) is derived to validate the effects of conjugate symmetry on GPS signal distortion. Both linear and circular array results are presented using the MSNWF. It is demonstrated that the MSNWF based preprocessor converges rapidly with low-sample support and low computational complexity.
Degree
Ph.D.
Advisors
Zoltowski, Purdue University.
Subject Area
Electrical engineering
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