A Detecting Algorithm Based on CAF for Overlapping  Frequency-Spectrum Multi-Signals

 For multi-signals detection of overlapping frequency-spectrum from different sources, a space-field detection algorithm is proposed in this paper based on Cross Ambiguity Function (CAF). Firstly, multi-signals are mapped to space-field through array of the signals’ CAF calculated in the two dimension searching area of time-delay and frequency-shift. Then, considering the characters of the multi-signals-CAF lobes and drawing from the idea of region-growing method in image segmentation, the signals are detected with iterative circulations by recognizing and segmenting the CAF lobes in accord with the signals one by one. Simulation is carried out to multi-signals with same frequency by the proposed algorithm. The detection probability curves under different Signal Noise Ratios and different Signal Power Ratios are presented. Likewise, the influence by different threshold coefficients to the detection probability and the fault alarm probability is given. The simulation results indicate that the algorithm may effectively detect different power multi-signals of overlapping frequency-spectrum under low SNR.