Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
158 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Enhanced RMT estimator for signal number estimation in the presence of colored noise (2211.12942v2)

Published 23 Nov 2022 in cs.IT, eess.SP, and math.IT

Abstract: The subspace-based techniques are widely utilized to estimate the parameters of sums of complex sinusoids corrupted by noise, and they need accurate estimation of the signal subspace dimension. The classic RMT estimator for model order estimation based on random matrix theory (RMT) assumes that the noise is white Gaussian, and performs poorly in the presence of colored noise with unknown covariance matrix. In order to deal with this problem, this paper proposes a novel algorithm to estimate the number of signals for the case of colored noise with unknown covariance matrix based on the analysis of the behavior of information theoretic criteria utilized in model order selection. Firstly, a first criterion is defined as the ratio of the current eigenvalue and the mean of the next ones, and its properties is analyzed with respect to the over-modeling and under-modeling. Secondly, a second criterion is designed as the ratio of the current value and the next value of the first criterion, and its properties is analyzed with respect to the over-modeling and under-modeling. Then, a novel enhanced RMT estimator is proposed for signal number estimation by analyzing the detection properties among the signal number estimates obtained by these two criteria and the RMT estimator to determine which eigenvalue is arising from a signal. Finally, simulation results are presented to illustrate that the proposed enhanced RMT estimator has better estimation performance and works better in the presence of colored noise than the existing methods.

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com