Weighted Direct Position Determination via the Dimension Reduction Method for Noncircular Signals

Abstract

This work studies the direct position determination (DPD) of noncircular (NC) signals with multiple arrays. Existing DPD algorithms of NC sources ignore the impact of path propagation loss on the performance of the algorithms. In practice, the signal-to-noise ratios (SNRs) of different observation stations are often different and unstable when the NC signal of the same radiation target strikes different observation locations. Besides, NC features of the target signals are applied not only to extend the virtual array manifold but also to bring high-dimensional search. For the sake of addressing the above problems, this study develops a DPD method of NC sources for multiple arrays combing weighted subspace data fusion (SDF) and dimension reduction (RD) search. First, NC features of the target signals are applied to extend the virtual array manifold. Second, we assign a weight to balance the error and obtain higher location accuracy with better robustness. Then, the RD method is used to eliminate the high computational complexity caused by the NC phase search dimension. Finally, the weighted fusion cost function is constructed by using the eigenvalues of the received signal covariance matrixes. It is verified by simulation that the proposed algorithm can effectively improve the location performance, get better robustness, and distinguish more targets compared with two-step location technology and SDF technology. In addition, without losing the estimation performance, the proposed algorithm can significantly reduce the complexity caused by the NC phase search dimension.

Direct Position Determination of Non-Circular Sources for Multiple Arrays via Weighted Euler ESPRIT Data Fusion Method

“…See Table 2 for other simulation parameters. Moreover, to show the heteroscedasticity of the received SNR at each observation station [36], we define 3 and M = 8 in Figure 4. The spectral peak diagrams show that NC-Euler-WESPRIT algorithm can successfully distinguish the targets even when the number of array elements at each observation station is less than that of targets.…”

Sparse Direct Position Determination Based on TDOA Information in Correlation-Domain

“…Studies by Mohammad and other scholars have shown that the DPD method has better positioning performance than the two-step method multipath and low SNR scenarios [5,6]. Direct positioning technology discretizes the space where the radiation source may exist.…”