Applications of modified adaptive affine projection predictor for global positioning system interference suppression

Abstract

The global positioning system (GPS) sensor has had a considerable impact on almost all positioning, navigation, timing, and monitoring applications. It provides spread spectrum satellite signals that can be processed in a GPS receiver, and it allows the receiver to estimate information about position, velocity, and time. A low-power GPS signal is susceptible to interference, which can seriously degrade receiver acquisition and tracking performance. Two kinds of modified affine projection filters, namely, variable step-size and dynamic selection structures, are presented for GPS jamming suppression applications. The variable step-size method based on the minimization of the mean square deviation is employed to achieve a higher convergence rate and a lower misadjustment error. The dynamic selection method can update the input vector by selecting a subset component and reduce computational complexity while offering a higher convergence speed. Suppression performance is evaluated via extensive simulation by computing the mean-squared prediction error (MSPE) and signal-to-noise ratio (SNR) improvements. Simulations show that our proposed methods can provide better performance than the conventional affine projection algorithm (APA) structures when severe interference-to-noise ratios (INRs) are experienced.