A chaotic radar system has been developed for through-wall detection and ranging of targets. The chaotic signal generated by an improved Colpitts oscillator is designed as a probe signal. Ranging to target is achieved by the cross-correlation between the time-delayed reflected return signal and the replica of the transmitted chaotic signal. In this paper, we explore the performance of the chaotic radar system for target detection and ranging through lossy media. Experimental results show that the designed chaotic radar has the advantages of high range resolution, unambiguous correlation profile, and can be used for through wall target detection and sensing.

An experimental wideband chaotic ground penetrating radar is proposed to locate underground pipes. A chaotic signal with a bandwidth of 1.56 GHz is utilized as the probe signal. The localization of the pipes is achieved by correlating the chaotic echo signal with its delayed duplicate and back-projection algorithm. Experimental results demonstrate that plastic pipe, metallic pipe, and multiple pipes can be located with a range resolution of 10 cm. Limited by the height of the sand, the detectable range is estimated to be 0.7 m for both the plastic pipes and the metallic pipes when the transmitting power is −12 dBm. The proposed system has the potential to detect buried pipes, and it is suitable for geological and civil engineering applications.

Chaos through-wall imaging radar has attracted wide attention due to its inherent low probability of detection/interception, strong anti-jamming, and high resolution. However, the target response is usually overwhelmed by strong clutter. This paper proposes an imaging-then-decomposition method based on two-stage robust principal component analysis (RPCA) to remove the clutter and recover the target image. The proposed method firstly focuses the energy of the preprocessing data by the back-projection imaging algorithm; then, it performs matrix decomposition on the full and the sparse component of the focused data, in succession, by the RPCA algorithm. Simulation and experimental results show that the proposed method can suppress the clutter dramatically and indicate human targets distinctly. Compared with the traditional methods, it has effectiveness and superiority in improving the signal-to-clutter ratio.

A high-resolution leaky coaxial cable (LCX) sensor for perimeter intrusion detection is proposed and experimentally demonstrated. In our proposed sensor system, a wideband Boolean-chaos signal is used as the probe signal, and a pair of leaky coaxial cables (LCXs) is applied for transmitting the probe signal and receiving the echo signal, respectively. By correlating the chaotic echo signal with its delayed duplicate and comparing the correlation traces before and after intrusion, the intruder can be accurately located. Experimental results demonstrate the proposed sensor can simultaneously detect multiple intruders. The range resolution reaches 30 cm, whilst the dynamic range can achieve 50 dB. In addition, this sensor possesses the excellent anti-interference performance to the noise and uncorrelated chaotic signal, which makes it show robust performance in the detection environment with noise or multiple chaotic LCX sensors cooperation.

A Golay-based ultra wideband ground penetrating for underground pipes location is proposed and experimentally demonstrated. Golay complementary codes with the code length of 1024 and frequency of 1 GHz are used as the probe signals. The two-dimensional image of the buried pipes is achieved by a correlation method and a back-projection algorithm. The experimental results show that both the plastic pipe and metallic pipe can be located with a range resolution of 10 cm. Furthermore, as the Golay complementary sequences are a pair of complementary sequences, the sum of their correlation function yields twice the value of the peak at the target position and zero elsewhere. Thus, compared with the stepped frequency signal radar or chaotic signal radar, the Golay-based radar can significantly improve the signal–noise ratio and has the capability of deep detection.

Chaotic laser radar based on correlation detection is a high-resolution measurement tool for remotely monitoring targets or objects. However, its effective range is often limited by the side-lobe noise of correlation trace, which is always increased by the randomness of the chaotic signal itself and other transmission channel noises or interferences. The experimental result indicates that the wavelet denoising method can recover the real chaotic lidar signal in strong period noise disturbance, and a signal-to-noise ratio of about 8 dB is increased. Moreover, the correlation average discrete-component elimination algorithm significantly suppresses the side-lobe noise of the correlation trace when 20 dB of chaotic noise is embedded into the chaotic probe signal. Both methods have advantages and disadvantages.