Biblio

Intentional interference presents a major threat to the operation of the Global Navigation Satellite Systems. Adaptive notch filtering provides an excellent countermeasure and deterrence against narrowband interference. This paper presents a comparative performance analysis of two adaptive notch filtering algorithms for GPS specific applications which are based on Direct form Second Order and Lattice-Based notch filter structures. Performance of each algorithm is evaluated considering the ratio of jamming to noise density against the effective signal to noise ratio at the output of the correlator. A fully adaptive lattice notch filter is proposed, which is able to simultaneously adapt its coefficients to alter the notch frequency along with the bandwidth of the notch filter. The filter demonstrated a superior tracking performance and convergence rate in comparison to an existing algorithm taken from the literature. Moreover, this paper describes the complete GPS modelling platform implemented in Simulink too.

Compressed sensing can represent the sparse signal with a small number of measurements compared to Nyquist-rate samples. Considering the high-complexity of reconstruction algorithms in CS, recently compressive detection is proposed, which performs detection directly in compressive domain without reconstruction. Different from existing work that generally considers the measurements corrupted by dense noises, this paper studies the compressive detection problem when the measurements are corrupted by both dense noises and sparse errors. The sparse errors exist in many practical systems, such as the ones affected by impulse noise or narrowband interference. We derive the theoretical performance of compressive detection when the sparse error is either deterministic or random. The theoretical results are further verified by simulations.