A method of indoor multi-path IR-UWB localization based on Bayesian compressed sensing

In order to solve the problem that high sampling rates of ADC which limit ultra-wideband (UWB) localization accuracy, a method of UWB localization based on Bayesian compressive sensing (BCS) was proposed. In the indoor multi-path environment, the transmission channel impulse response is estimated accurately using the proposed approach, then we adopt the method of direct path (DP) detection to estimate the time of arrival (TOA) which can be used to calculate the transmission delay, finally, the target location can be located by the weighted least square (WLS) algorithm. From the simulation results, we find that the proposed method compared with the traditional localization algorithm not only the localization accuracy is guaranteed, but also the ADC sampling rate is reduced, at the same time, it is advantageous that compressive sensing (CS) method applied in the UWB localization system.