Symmetric thinned coprime array with reduced mutual coupling for mixed near‐field and far‐field sources localization

Abstract

As we all know, the non‐uniform array is widely used in the mixed near‐field (NF) and far‐field sources localization. The nested array contains a uniform linear array, it is easy to be affected by mutual coupling, so we propose a symmetric thinned coprime array (STCA) to reduce the mutual coupling effect of mixed source localization. In this paper, the STCA configuration consists of two sparse uniform linear arrays, the first subarray is composed of 2N − 1 sensors, and the sensor element spacing is Md. The second subarray is composed of 2M+2⌊M2⌋ $2M+2\lfloor \frac{M}{2}\rfloor $ sensors, and the sensor element spacing are Nd and Md respectively. The two subarrays form the symmetric coprime array, which shares a reference sensor. Under the same number of physical array sensors, compared with the latest symmetric nested array, although STCA has lower consecutive lags, the array sensors have larger inter‐sensor spacing and larger physical array aperture, which can significantly reduce the mutual coupling effect between physical sensors, and better estimation performance of direction‐of‐arrival (DOA) estimation can be achieved. Finally, simulation results show that STCA can achieve better performance than other symmetric nested arrays under the same array sensors and mutual coupling effects.

Improved symmetric flipped nested array for mixed near‐field and far‐field non‐circular sources localization

“…To better quantify the performance of ISFNA, we compare it with SNA [31], SDNA [32], ISNA [33] and SFNA [30] in two aspects: consecutive lags and mutual coupling coefficient [34] for different numbers of physical sensors, Q . In particular, Figure 3 shows the structure of SFNA and ISFNA, showing the difference between SFNA and ISFNA more clearly.…”

“…In this section, the estimation method of mixed-field NC signal was discussed. Using a special cumulant matrix and a spatial smoothing MUSIC (SS-MUSIC) algorithm to obtain all DOAs; then, brought it into the range function, and solved the range parameter through a 1-D spectral search [25,30,34].…”

Symmetric flipped nested array for mixed near‐field and far‐field non‐circular source localisation

“…In this section, we discuss the NC source localisation methods for the DOAs and estimate the ranges. We used a special cumulant matrix and a spatial smoothing subspace MUSIC (SS-MUSIC) algorithm to obtain all DOAs; then, we use the estimated DOA, bring it into the range function, and solve the range parameter through a 1-D spectral search [25,35].…”

A Novel Low-Complexity Method for Near-Field Sources Based on an S-IMISC Array Model

“…Wang et al [29] proposed an enhanced symmetric nested array model (ESNA) for mixed-signal parameters. Wang et al [30,31] proposed a novel symmetric flipped nested array (SFNA) and an improved symmetric flipped nested array (ISFNA) for mixed-signal parameter estimation. The above im-proved nested array models can achieve higher DOF.…”