This paper presents a three-dimensional (3D) spatial localization algorithm by using multiple one-dimensional uniform linear arrays (ULA). We first discuss geometric features of the angle-of-arrival (AOA) measurements of the array and present the corresponding principle of spatial cone angle intersection positioning with an angular measurement model. Then, we propose a new positioning method with an analytic study on the geometric dilution of precision (GDOP) of target location in different cases. The results of simulation show that the estimation accuracy of this method can attain the Cramér-Rao Bound (CRB) under low measurement noise.

In order to improve the frequency band utilization and avoid mutual interference between signals, the BD3 satellite signals adopt Binary Offset Carrier (BOC) modulation. On one hand, BOC modulation has a narrow main peak width and strong anti-interference ability; on the other hand, the phenomenon of false acquisition locking caused by the multi-peak characteristic of BOC modulation itself needs to be resolved. In this context, this paper proposes a new BOC(n,n) unambiguous acquisition algorithm based on segmentation reconstruction. The algorithm is based on splitting the local BOC signal into four parts in each subcarrier period. The branch signal and the received signal are correlated with the received signal to generate four branch correlation signals. After a series of combined reconstructions, the final signal detection function completely eliminates secondary peaks. A simulation shows that the algorithm can completely eliminate the sub-peak interference for the BOC signals modulated by subcarriers with different phase. The characteristics of narrow correlation peak are retained. Experiments show that the proposed algorithm has superior performance in detection probability and peak-to-average ratio.