Design of Evolutionary Adaptive Notch Filter for GPS Anti-Jamming System

GPS signals can be affected easily by interference due to the low power of signals and the long way between the satellites and receivers. Interference cancellation is one of the major challenges in using GPS. One of the most common intentional interferences is Continuous Wave Interference (CWI) jamming and the most popular way to reduce the impact of it on the GPS signal is using an Adaptive Notch Filter (ANF). Two kinds of heuristic Evolutionary Algorithms (EAs) are used to design second-order IIR Evolutionary Adaptive Notch Filter (EANF). The first algorithm is the Genetic Algorithm (GA) and the second one is Particle Swarm Optimization (PSO) algorithm. EAs are used to find answers to the problems in which there is no specific solution, and this is exactly what is needed to fix the digital filter design problems. NF is implemented in FPGA hardware according to the obtained filter coefficients. Finally, the efficiency of the proposed methods is compared with similar methods in terms of different evaluation metrics. The simulation results show about 12% SNR improvement by using GA and 97% RMS improvement by using the PSO method for higher than 50-dB JSRs.

Automated summary

GPS signals can easily be interfered with, and interference cancellation is a major challenge. The use of an Adaptive Notch Filter helps reduce the impact of interference on GPS signals. Heuristic Evolutionary Algorithms are used to design and implement the filter in hardware.