Research On Key Technologies Of Dsss Signal Acquisition In Complex Conditions

As the development of technology in the satellite navigation and TT&C field,the acquisition technology under complex conditions,such as in the presence of interference,signals in high dynamic scenarios,and signal with large power range,needs to be further improved.In this paper,the acquisition technology of direct sequence spread spectrum(DSSS)signals under complex conditions is researched.The main contents and contributions are concluded as follows:1.For the acquisition of DSSS signals under multiple-access interference(MAI)scenarios,two MAI mitigation algorithms based on reiterative minimum mean square error(RMMSE)are proposed.Firstly,the model of DSSS signals with continuous-waveform characteristics,which is suitable for RMMSE process,is provided.Secondly,based on the DSSS signal model,the coefficients of RMMSE filter in the adaptive pulse compression method are modified according to the correlation relationship of elements in the complex amplitude matrix,and then an anti-MAI acquisition algorithm with the modified RMMSE(M-RMMSE)is proposed.M-RMMSE algorithm requires large-scale matrix operation which leads to huge computational load.To solve this problem,an anti-MAI acquisition algorithm via RMMSE based on matched filter outputs is proposed sequentially.This algorithm makes full use of the pseudo-code correlation characteristic,and then filters the matched filter outputs via RMMSE filter with reduced stage-number;therefore,achieves a notable computational load decreasing.At last,the proposed algorithms are verified by simulations.It is shown that the proposed two algorithms effectively mitigate the strong MAIs.2.Long-term energy accumulation is required in weak signal acquisition,which is susceptible to signal dynamic and data modulation.To solve this problem,four dynamic focusing algorithms that can deal with the data modulation are proposed based on existing dynamic focusing algorithms in the field of radar signal processing.Firstly,the influence of any order dynamic on coherent accumulation is quantitatively analyzed,which is the extension of the existing research results in terms of the dynamic order.The research results provide theoretical basis for the dynamic order modeling of received signal and the selection,designation and performance evaluation of the dynamic focusing algorithms.Secondly,to meet with the requirement of the weak signal detection,the generalized Radon Fourier Transform(GRFT)and Keystone transform-Lv transform(KT-LVT)dynamic focusing algorithms are selected and extended to the DSSS signal processing field.Four kinds of dynamic focusing algorithms that can deal with the data modulation are proposed based on the GRFT and KT-LVT algorithm,which is: the GRFT algorithm with the data symbol prediction and position expectation of data bit transition,the GRFT algorithm with non-coherent accumulation,the anti-data bit transition KT-LVT algorithm with confined maximum delay time,and the anti-data bit transition KT-LVT algorithm with squared operation.The output signal-to-noise ratio and computational load of the proposed four algorithms are analyzed.At last,the validity of the proposed algorithms and the correctness of the deduced formulas are verified by simulations.The developed algorithms are effective countermeasures against the sign transition in the case of a long integration time for weak DSSS signals in high dynamics.3.Under complex conditions such as in the presence of interference and signal with large power range,the false-alarm probability of conventional acquisition algorithm caused by high local side-lobes is increased.To solve this problem,an acquisition algorithm based on whole-region search strategy is proposed in this paper.Furthermore,to reduce the mean acquisition time of the proposed algorithm,an acquisition algorithm with the whole-region search strategy cooperated by the detection with adaptive parameter adjustment is proposed.In the proposed algorithm,the pre-detection signal-to-noise ratio,which is estimated during the search process,is used to adjust the threshold and the parameter of detector for the following cells.The calculation formulas of detection probability,the false-alarm probability,and the mean acquisition time are derived and verified by simulations.The simulation result show that the proposed algorithm can decrease the false-alarm probability by whole-region search;and speed up the acquisition process by detection with adaptive parameter adjustment.