In this paper, we combine the multiple-input-multiple-output (MIMO) array antenna technology with a multipolarization component in a ground penetrating radar (GPR) system to improve target detection accuracy. The MIMO technology introduced in previous literature is widely applied in radar and other wireless communication fields. Here, we apply the MIMO technology with a “plane-wave like” (PWL) source that uses array antennas with small spacing to emit a pulse source at the same time in GPR detection. First, we analyze the physical mechanism of the MIMO GPR system with a “PWL” source to improve the target detection resolution. Then, we carry out a numerical simulation with a finite-difference time-domain method in 1-D and 2-D array antennas to compare the imaging results of the MIMO and traditional GPR systems. Finally, the synthetic data MIMO GPR experiment with a step-frequency GPR system is implemented. Compared with the traditional GPR system, our results demonstrate that the MIMO GPR system with a multipolarization detection mode can overcome the influence of target radar cross sections and antenna radiation directions, and improve target detection accuracy effectively. Meanwhile, the synthetic MIMO GPR system also provides a good idea to improve the system performance and reduce system design requirements and the manufacture cost.

Ultrawideband (UWB) radar technology has emerged as one of the preferred choices for through-wall detection due to its high range resolution and good penetration. The resolution is a result of high bandwidth of UWB radar and helpful for better separation of multiple targets in complex environment. Detection of human targets through a wall is interesting in many applications. One significant characteristic of human is the periodic motion, such as breathing and limb movement. In this letter, we apply the UWB radar system in through-wall human detection and present the methods based on fast Fourier transform and S transform to detect and identify the human's life characteristic. In particular, we can extract the center frequencies of life signals and locate the position of human targets from experimental data with high accuracy. Compared with other research studies in through-wall detection, this letter is concentrated in the processing and identifying of the life signal under strong clutter. It has a high signal-to-noise ratio and simpler to implement in complex environment detection. We can use the method to search and locate the survivor trapped under the building debris during earthquake, explosion, or fire.

The ultra wideband (UWB) radar has greater advantage in estimate positions and shapes of the target in Through Wall Imaging (TWI). One significant characteristic of human beings is the periodic motion, such as respiration and movement of arms. In this paper, we apply the UWB pulse radar to detect the periodic motion in through-wall detection. We present methods based on the FFT and time-frequency analysis to detect periodic motions characters using the TWI data. In particular, we extract the frequency of the periodic motion, characterize time-frequency features, the size and position of the human being from the TWI images. It is straight forward to use the method in other applications such as earthquake and fire rescue.