A low complexity acquisition algorithm for DSSS signal with low SNR and non-coherent data modulation

A block acquisition algorithm based on parallel interval estimation is proposed for direct sequence spread spectrum (DSSS) signal with low signal-to-noise ratio (SNR) and non-coherent data modulation. First, the existence interval of data modulation offset is estimated in parallel with invalid data section abandoned against possible bit-flip. Then fast Fourier transform (FFT) and incoherent accumulation are adopted in the valid data sections of each estimation branch to acquire cumulative detection value of each frequency point. Finally, the constant false alarm rate detection and parabolic interpolation are performed on the maximum cumulative detection value to fulfill signal detection and parameter estimation. Both analysis and simulation demonstrate that by adjusting key parameters to match the requirement of false alarm and detection probability, acquisition time and SNR, the proposed algorithm achieves good performance with low computational complexity and resource consumption.