A Nonlinear Code Tracking Filter for GPS-Based Navigation

Abstract

Current Global Positioning System (GPS)-based navigation systems are highly susceptible to unintentional and intentional jamming due to relatively low signal power at the receiver antenna and, in part, due to suboptimal code tracking loop designs that do not account for measurement nonlinearities near loss-of-lock. A nonlinear code tracking filter is developed whose architecture is based on a rigorous minimum-variance solution of the navigation problem, rather than using prespecified tracking loop architectures. The filter implementation can be viewed in terms of the classical notions of error detector functions, which depend on signal-to-noise ratio (SNR) and root mean square (rms) code tracking error. Detector functions are defined for both code tracking error and code tracking error variance. The filter responds more rapidly than current designs to rapidly varying jammer power due to a measurement-dependent term in the covariance calculations. Extended-range tracking is utilized, yielding linear state vector error detector functions (i.e., the filter is essentially optimum) out to the maximum allowed by the correlator range, and reducing the need for reacquisition. Significant antijam improvements relative to current designs are predicted from high-fidelity simulation and hardware demonstrations. Computational requirements are comparable to extended Kalman filter/vector tracking loop techniques.