In recent years, a new non-contact life detecting device has been developed, known as life-detection radar, which can measure bodily movement and locate human subjects. Typically, the amplitude of the vibration being measured is quite small, so the measurement is easily contaminated by noise in the radar system. To date, there is no effective index for judging the influence of noise on the vibration measurements in this radar system. To solve this problem, in this paper, we define the micro-Doppler measurement sensitivity to analyze the influence of noise on the measurement. We then perform a simulation to generate a performance curve for the radar system.

Extracting periodic heartbeat signals based on the traditional Fourier transform using a noncontact bio-radar is difficult because chest displacements caused by the heart are much smaller than those caused by respiration. Normally, they can be separated using the continuous wavelet transform; however, the miniscule difference of wavelet scale selection under different conditions may influence the separation performance to some extent. To solve this problem, this study proposes a method based on signal-to-noise ratio calibration to adaptively select the Morletdyadic wavelet scales and then separate the heartbeat signal from the respiration one using the selected scales, which can be applied to detect vital signs of different conditions. The experimental results have exhibited the accuracy and feasibility of the proposed method.

Because of the mutual interference between multiple stationary humans, distinguishing individuals via the range profile of a single-channel bioradar is difficult. To solve this problem, we used an Ultra-WideBand Multiple-Input Multiple-Output (UWB MIMO) bioradar to compose high-resolution two-dimensional images. These images allow multiple stationary humans to be separated from space. Then, vital signs are enhanced on the basis of the UWB MIMO image sequence, thereby leading to effective suppression of interference. The experimental results demonstrate that the proposed method can compose high-resolution images of multiple stationary humans. Thus, high-performance detection and localization of multiple stationary humans can be expected.

Speech signal acquisition is of great significance for human communication. Bio-radar technology has many advantages, such as it is noncontact, noninvasive, safe, highly directional, highly sensitivity, immune to strong acoustical disturbance and penetrable. This technology has important applications in the field of speech detection. In this paper, we first review the developmental history of speech detection technology, and then summarize the status of bio-radar speech detection technology. The basic principles of a bio-radar in detecting speech signals are given, and the performance of three types of bio-radar speech detection systems are compared in this paper. Finally, the potential applications of bio-radar speech signal detection technology are prospected.

An optimal waveform design method that fully employs the knowledge of the target and the environment can further improve target detection performance, thus is of vital importance to research. In this paper, methods of radar waveform optimization for target detection are reviewed and summarized and provide the basis for the research.

Sea clutter is one of the main limiting factors influencing the target detection performance of nautical radars. The physical mechanism of sea clutter is complex with an abundance of influencing factors, and the non-Gaussian as well as non-stationarity behavior is significant. Thus, research into sea clutter property cognition is complicated and has to be systematic. Based on research that concentrates on experimental data, this paper reviews and summarizes the research developments in sea clutter property cognition. It concentrates on the properties that are of most interest for target detection algorithms:amplitude distribution, spectra, correlation, and non-stationarity and nonlinearity. The main research results are also concluded. Based on this, four aspects of problems that need further exploration are highlighted and include the following:further analysis of sea clutter influencing factors; the game problem between sea clutter precision modeling and the requirements of detection algorithms; and the property cognition between radar target and sea clutter.

The unified theoretical frame of a joint transmitter-receiver reduced dimensional Space-Time Adaptive Processing (STAP) method is studied for an airborne Multiple-Input Multiple-Output (MIMO) radar. First, based on the transmitted waveform diverse characteristics of the transmitted waveform of the airborne MIMO radar, a uniform theoretical frame structure for the reduced dimensional joint adaptive STAP is constructed. Based on it, three reduced dimensional STAP fixed structures are established. Finally, three reduced rank STAP algorithms, which are suitable for a MIMO system, are presented corresponding to the three reduced dimensional STAP fixed structures. The simulations indicate that the joint adaptive algorithms have preferable clutter suppression and anti-interference performance.

Increasing the coherent integration time of the signal can improve the detection of weak targets. The key to the long-time coherent integration for bistatic radar is to solve the target motion compensation from echoes with nonlinear phases. Neglecting the effect of the crossing beam, the compensation of the Radon-Fourier Transform (RFT) was studied in the range and velocity fields. In addition, the method can be operated in the frequency domain. The range walk correction and pulse accumulation were completed by jointly searching along the bistatic range and velocity parameter space. The proposed method was verified by theoretical analysis and simulations.

To overcome the disadvantages of a non-cooperative frequency hopping communication system, such as a high sampling rate and inadequate prior information, parameter estimation based on Blind Compressed Sensing (BCS) is proposed. The signal is precisely reconstructed by the alternating iteration of sparse coding and basis updating, and the hopping frequencies are directly estimated based on the results. Compared with conventional compressive sensing, blind compressed sensing does not require prior information of the frequency hopping signals; hence, it offers an effective solution to the inadequate prior information problem. In the proposed method, the signal is first modeled and then reconstructed by Orthonormal Block Diagonal Blind Compressed Sensing (OBD-BCS), and the hopping frequencies and hop period are finally estimated. The simulation results suggest that the proposed method can reconstruct and estimate the parameters of non-cooperative frequency hopping signals with a low signal-to-noise ratio.

Circular Synthetic Aperture Radar (CSAR) can acquire targets' scattering information in all directions by a 360° observation, but a single-track CSAR cannot efficiently obtain height scattering information for a strong directive scatter. In this study, we examine the typical target of the three-dimensional circular SAR interferometry theoryand validate the theory in a darkroom experiment. We present a 3D reconstruction of the actual tank metal model of interferometric CSAR for the first time, verify the validity of the method, and demonstrate the important potential applications of combining 3D reconstruction with omnidirectional observation.

In this study, we present a modified full-aperture imaging algorithm that includes scalloping correction and spike suppression for sliding-Mosaic-mode Synthetic Aperture Radar (SAR). It is innovational to correct the azimuth beam-pattern weighting altered by radar antenna rotation in the azimuth during the de-ramping preprocessing operation. The main idea of spike suppression is to substitute zeros between bursts with linear-predicted data extrapolated from adjacent bursts to suppress spikes caused by multiburst processing. We also integrate scalloping correction for the sliding mode into this algorithm. Finally, experiments are performed using the C-band airborne SAR system with a maximum bandwidth of 200 MHz to validate the effectiveness of this approach.