The thickness estimation of the top surface layer and surface layer, as well as the detection of road defects, are of great importance to the quality conditions of asphalt pavement. Although ground penetrating radar (GPR) methods have been widely used in non-destructive detection of pavements, the thickness estimation of the thin top surface layer is still a difficult problem due to the limitations of GPR resolution and the similar permittivity of asphalt sub-layers. Besides, the detection of some road defects, including inadequate compaction and delamination at interfaces, require further practical study. In this paper, a newly-developed vehicle-mounted GPR detection system is introduced. We used a horizontal high-pass filter and a modified layer localization method to extract the underground layers. Besides, according to lab experiments and simulation analysis, we proposed theoretical methods for detecting the degree of compaction and delamination at the interface, respectively. Moreover, a field test was carried out and the estimated results showed a satisfactory accuracy of the system and methods.

Ultra‐wideband (UWB) radar is widely used in static through‐wall imaging (TWI). There are still many imaging problems of motion through‐wall targets for complex system structure and unknown wall environment. Herein, a motion compensation method based on the reference channel and a modified Kirchhoff migration imaging algorithm are proposed for Ultra‐wideband (UWB) MIMO sparse array, which is used for high‐precision 3D TWI of moving targets. The channels of the MIMO radar are time‐division multiplexing based on microwave switch. Besides, a reference channel is added for motion compensation of moving targets. Performing motion compensation on the target before 3D imaging can effectively avoid the problems of defocus and position deviation caused by target motion. In the proposed imaging method, the backward Green function is used to replace the forward Green function to solve the problem of a large field of view with small arrays. The experiment with a static through‐wall target proves that the proposed imaging algorithm can suppress sidelobes well compared with the traditional back‐projection algorithm (BPA). Through‐wall experiments are carried out for targets with different speeds, and results show that the positioning accuracy and sidelobe level of the proposed compensation method is better than previously proposed methods.

In actual life-detection radar applications, a quasi-static person with weak respiration is difficult to find when relying on the echoes from a single fixed observation point. To effectively sense the weak respiration of a quasi-static person in complex through-wall and through-floor conditions, this paper proposes a novel multi-observation point detection system composed of multiple Golay complementary coded radars in which communication and synchronization are carried out wirelessly. The collaboration structure and Golay complementary coded transmitter improve the signal to noise ratio (SNR). Proof-of-principle experiments are carried out with our designed radar prototype and prove that the radar system can detect a respiring target 21 m behind a brick wall or a respiring target behind two levels of reinforced concrete floors, validating the effectiveness of a multi-observation point working mode for the efficient detection of weak human respiration.