Quantized Compressed Sensing Based TOA Estimation of IR-UWB System in the Presence of Overload Noise

Abstract

In this paper, the problem of the overload noise during quantization step applied to the compressed sensing (CS) measurements is tackled for Impulse Radio (IR) Ultra-Wide Band (UWB) ranging signal under indoor residential environment. The dynamic-threshold (DT) fitting method used for the high precision of the time of arrival (TOA) estimation is leveraged in the case of the bounded non sparse noises like thermal noise and quantization noise. However, the inevitable presence of the overload noise in the practical application decreases significantly the ranging accuracy with the dynamic-threshold method whose parameters are established without considering the saturation effect of the measurements. The fact that the overload noise is sparseness motivates us to focus on this special characteristic. Hence, the proposed approach aims to reduce the overload noise effect on the reconstruction of the channel impulse response (CIR) through justice pursuit de-noising (JPDN) model and allows the use of the dynamic-threshold method for TOA estimation. The paper exploits the innovative basis pursuit de-noising (iBPDN) strategy to reduce computational load. The performances of the proposed approach are verified through numerical simulations.