Wall Position Estimation for FMCW Radar Indoor Tracking

To tackle the challenge of multipath effects in FMCW radar systems used for indoor tracking, which can lead to ghost images and impede target detection, this paper presents a two-stage approach to address this issue. First, a linear identification method based on the Random Sample Consensus (RANSAC) algorithm is applied in the Range-Doppler domain to differentiate between the true target and second-order ghost images. By leveraging the inherent mirror symmetry relationship between the true target and ghost images, a least squares method is then proposed to optimally estimate the wall position. Experimental results demonstrate the efficacy of this approach, achieving a wall position estimation accuracy with an overall error of 1.1°, thereby enabling reliable wall location estimation.