Phase ambiguity resolution algorithm based on vector baseline fusion

To address the phase ambiguity difference problem encountered when narrowband signals are used for localization in uniform circular array based ultra-short baseline systems, this paper proposes a vector baseline fusion algorithm based on the parallel baseline algorithm. First, the concept of pseudo-ambiguity number is introduced, and the vector constraint condition for the baseline phase difference of uniform circular arrays is established. Adjacent short baselines are paired with corresponding long baselines to form multiple groups of baseline combinations, and the pseudo-ambiguity number set for each group is calculated based on the phase of the received signal. Second, a step-by-step search method is adopted: the number of candidate combinations retained after preliminary screening is determined according to the number of array elements, and candidate pseudo-ambiguity numbers for each baseline are obtained through screening. Then, a comprehensive loss function integrating phase difference error and time delay sign constraint is constructed. After setting appropriate weight values, global optimization is performed on all candidate combinations, and the optimal pseudo-ambiguity number combination is finally obtained through solution. Simulation results show that at a signal-to-noise ratio of −10 dB, the success probability of ambiguity resolution of the proposed algorithm is 44.7% higher than that of the parallel baseline algorithm. Lake test results indicate that at operating distances of 300 m and 700 m, the ambiguity resolution success rate of the algorithm reaches 98.7% and 92.6% respectively, demonstrating favorable robustness and engineering practicability in real underwater environments.