# Radar Target Localization with Multipath Exploitation in Dense Clutter Environments
## 1 Introduction  
Target localization in urban areas is an important requirement for both military and civilian applications, such as emergency rescue, security surveillance and intelligent transportation. A variety of techniques has been developed to detect and locate targets, including vision cameras, sonars, lidars and radars [1]. The all-time and all-weather advantages make radar an irreplaceable part of these techniques. However, dense buildings become obstacles to radar electromagnetic (EM) waves, which make EM waves propagate through not only the line-of-sight (LOS) path but also non-line-of-sight (NLOS) paths, such as reflection, diffraction and transmission. Radar systems commonly acquire range and angle measurements from time-of-arrival (TOA) [2, 3] and direction-of-arrival (DOA) [4, 5] of echo signals as LOS path returns. However, the lengths of received NLOS signals are longer than the range of the direct path from radar to the target in multipath propagations, and the received DOA of NLOS signals are different from the DOA of LOS path. Therefore the NLOS propagations lead to considerable errors in range and angle measurements in multipath scenarios [6]. The performances of classic radar target localization methods based on LOS geometry of free space propagation degrade significantly in such multipath environments. To mitigate the multipath effect, multiple techniques have been proposed. Conventional researchers consider multipath signals as clutter and attempt to separate multipathsignals from the received signal so that only the LOS signal is applied for further processing [7; 8]. However, multipath signals propagated through NLOS paths provide extra spatial information that can be utilized to detect and locate targets. Early studies in constrained multipath scenarios demonstrated the possibility and effectiveness of multipath exploitation where the fixed multipath propagation can be modeled via analytical geometry methods [9; 10; 11; 12]. A typical application is the over-the-horizon radar (OHTR) where EM waves are reflected by ionosphere layers at different heights. Classic data association methods (e.g., joint probabilistic data association filter (JPDAF), probabilistic multi-hypothesis tracker (PMHT) and probability hypothesis density (PHD) filter) combined the analytical geometry reflection model with unknown height have been proposed to improve the performance of OHTR target tracking problem [13; 14; 15; 16; 17]. Through-the-wall radar is another application that exploits the transmission of EM waves to detect and locate targets behind the wall [18; 19; 20]. In urban environments, a common task is indoor positioning which locates a target in the presence of both LOS and NLOS signals [21; 22]. In this case, the NLOS signal reflected by obstacle walls is equivalent to the bistatic radar geometry model where a signal is transmitted from the radar tothe target and received by a virtual radar mirrored on the reflecting wall with the original radar. Therefore, target localization can be derived from the LOS path combined with the NLOS paths using the bistatic radar geometry without extra radar sources. In [23], the propagation path and wall association algorithm is proposed to associate multipath TOA signals to their corresponding reflecting obstacles, and target localization is derived by a non-linear least squares (NLS) optimization. The Cramer-Rao bound of the TOA-based multipath localization method is given in [24] to analyze the localization performance of radar at different places and obtain the optimal radar position setup in the given scenario. In [25], directional constraints are introduced to ultra-wideband radar for indoor positioning tasks to improve location accuracy in the absence of some NLOS paths. [PERSON] et al. [26] proposed a multi-target location method based on target association hypothesis and consistency checking. Another typical task in urban areas is to detect targets behind the corner, where the LOS path does not exist and only reflected signals can be obtained [27; 28].