Research On The Anti-jamming With Adaptive Arrays In DSSS Receivers

The spreading spectrum has a strong anti-jamming ability, but sometimes in the presence of strong jammers, it is difficult to suppress the jammers effectively by only the processing gain. Therefore, it is necessary to study other anti-jamming techniques. This thesis focuses on the research on the space domain anti-jamming and the space-time domain anti-jamming techniques based on the adaptive arrays in the DSSS receiver. The main contributions are listed as follows:1. The space domain anti-jamming performance of the power inversion (PI) array is studied. The emphases are put on the realization of the PI array using LMS algorithm and RLS algorithm and the anti-jamming ability of the PI array in different occasions, including different number, strength and bandwidth of jammers. The simulation results show that the PI array with M-element can suppress M-1jammers at most. The stronger the jammer is, the better the effect of anti-jamming is. The array can separate the jammers only through the space domain, so it can not distinguish jammers with different bandwidth apart.2. A particle swarm optimization (PSO) algorithm is put forward to realize the PI array. The LMS, RLS and PSO algorithms are compared with attention being paid to the convergent speed and convergence performance. The simulation results show that the LMS algorithm has small computational complexity, but it can not improve the convergent speed and steady-state misadjustment error simultaneously. The RLS algorithm has a fast convergence speed, but it bears a burden of large computation. The PSO algorithm can obtain a balance between the convergent speed and computation.3. The anti-jamming space-time adaptive filtering technique is studied. It has the advantages of both space-only processing and time-only processing. The wideband jammers and narrowband jammers can be suppressed simultaneously. Due to the large dimensionality of the space-time correlation matrix relatived to space correlation matrix, a multi-stage nested wiener filter (MSNWF) algorithm is adopted to reduce the dimensionality in the thesis. The simulation results show that the space-time adaptive processing with M-element can suppress more than M-1jammers and separate the jammers through the space domain and frequency domain. Therefore, space-time adaptive processing can suppress the jammers more exactly.