Frequency Spectrum Estimate Based on Decomposed FLOC Matrix under Stable Distribution Noise

Abstract

The radar work in a complex environment where the noise has very strong pulse, the noise can be described by stable distribution. The conventional spectrum estimation method based on second order statistics is reasonable in many cases, however, the performance of the conventional algorithm degenerate in stable distribution environment. We propose three new frequency spectrum estimate method with Fractional lower order covariance (FLOC), FLOC-Pisarenko method, FLOC-Esprit method and FLOC multiple signal classification (FLOC-MUSIC) method. The conventional spectrum estimation methods with three proposed methods under Gaussian noise and stable distribution are compared in this paper, simulations show that the conventional methods degenerate, but the proposed algorithms can work better in stable distribution environment, and are robust.

The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise

“…Since the MUSIC algorithm fails to effectively identify coherent signal sources, the spatial smoothing method [11] is used in the following comparison algorithms. The comparison algorithms being compared include ROC-SSMUSIC [22], FLOM-SSMUSIC [24], FLOC-SSMUSIC [27], and IN-SSMUSIC [31].…”

“…In the literature [24][25][26], the FLOM-MUSIC algorithm based on the fractional lower-order moment (FLOM) was proposed. In the literature [27][28][29], a fractional lower-order cyclic MUSIC (FLOC-MUSIC) algorithm using a fractional lower-order cyclic covariance matrix was proposed. However, these FLOS-based algorithms require prior knowledge of the characteristic exponent of stable distribution.…”

“…Compared with the algorithm in the literature [27][28][29][30][31], the algorithm in this paper does not require large sample sampling and loop iterations, so the computational complexity is low; 3.…”