Non‐Line‐of‐Sight Target Localisation Using Multipath Signal in Urban Areas

ABSTRACT

With the acceleration of urbanisation, the ability to detect target information in urban blind areas is urgently needed in many fields such as smart cities and autonomous driving. However, existing nonline‐of‐sight (NLOS) target localisation methods mainly assume that the urban building walls are flat with ideal reflections. This simplification results in significant localisation errors in real‐world scenarios, where wall surfaces include concave–convex features such as balconies and windows. To address this issue, we propose a joint estimation algorithm for target position and wall parameters based on the single‐input‐single‐output (SISO) radar system. First, we parameterise the concave–convex features of the walls at reflection points and incorporate them into the multipath echo model based on the sparsity of the scene. Then, an objective function is constructed by minimising the error between the echo signal and the signal reconstructed using compressed sensing. Furthermore, the alternating direction method of multipliers (ADMM) and genetic algorithms are designed for hierarchical optimisation. Finally, extensive simulations and experiments demonstrate that the proposed algorithm can achieve high‐precision NLOS target localisation in irregular wall surfaces.