Detection Fusion of Weak Signal under Chaotic Noise Based on Distributed System

Shengli Zhao,Liyun Su,Lizhi Zhang,Antonio Lazaro

doi:10.1155/2021/5597841

Abstract

In this paper, the problem of signal detection under chaotic noise was considered in the distributed detection fusion system. The problem which is urgent and difficult has important research value. A new detection and fusion mechanism for weak signal under chaotic noise based on a distributed system is proposed. Due to the short-term predictability of chaotic signals and their sensitivity to small disturbances, observation of each local sensor is reconstructed in phase space according to the Takens delay embedding theorem. The locally weighted regression (LOWESS) model is used to fit the observation of each local sensor in the phase space. Thus, the chaotic noise is stripped out from the observation, and the fitting error without chaotic noise is regarded as the new observation of each local sensor. Based on the new observation without chaotic noise, an optimization model aiming at minimizing the Bayesian risk of the fusion center is established. Under the condition that the observations of local sensors are conditionally independent, the fusion rule and the sensor decision rules are derived. An algorithm is proposed to obtain the fusion rule and local decision rules. The simulation results show that the proposed signal detection and fusion algorithm can effectively detect weak signals under chaotic noise background. Specifically, the fusion performance is obviously better than that of local sensors with low SNR.

Highlights

Weak signal is a weak quantity which is difficult to be detected. It refers to the signal with a low signal-to-noise ratio (SNR) which is submerged by noise [1, 2]
The specific idea of weak signal detection and fusion is as follows: first of all, the observation of each local sensor was reconstructed in phase space, and the locally weighted regression (LOWESS) model was used to divest the chaotic noise
In order to further illustrate the advantages of distributed detection fusion system under chaotic noise, its performance is analyzed under different parameter values

Summary

Introduction

Weak signal is a weak quantity which is difficult to be detected. It refers to the signal with a low signal-to-noise ratio (SNR) which is submerged by noise [1, 2]. The specific idea of weak signal detection and fusion is as follows: first of all, the observation of each local sensor was reconstructed in phase space, and the LOWESS model was used to divest the chaotic noise. The problem of detecting weak signal under chaotic noise by local sensors can be abstracted into the following hypothesis test problem: H0 : ykðtÞ = cðtÞ + nkðtÞ, ð1Þ. H∗1 : ykðtÞ − cðtÞ = nkðtÞ + sðtÞ: The hypothesis test of local sensors in distributed detection fusion system under chaotic noise is proposed. It provides the hypothesis basis for the phase space reconstruction of the observation signal and the construction of the local weighted regression model in the part.

Detection Fusion Optimization Model and Its Solutions

C F PðujH 0 Þ CDPðujH1Þ

Simulations

Conclusions