Research On Micro-motion Target Detection Method Based On OFDM Terahertz Detection And Communication Integration Signal

Communication and detection devices have a wide range of applications in both the civilian and military sectors.In scenarios such as battlefields,connected vehicles and smart homes,there is a need for detection functions as well as communication functions.Traditionally,detection and communication are handled as two separate devices.The detection and communication integration is to replace the two systems of detection and communication with one system that shares the transmitting signal,the reception and the subsequent signal processing.This reduces the size and power consumption of the system and increases the spectrum utilisation,which is of great research importance.The thesis addresses the background of OFDM detection and communication integration signals in the terahertz band,and carries out research on micro-motion target detection methods based on OFDM detection and communication integration signals.The main research elements are as follows:Firstly,the transmit signal model of the integrated system of detection and communication is developed based on the OFDM signal characteristics.Further,the echo model of the integrated signal is derived.The detection advantages of OFDM integrated signals are discussed from the perspective of fuzzy functions.A foundation is laid for the subsequent research on detection as well as target micro-motion feature extraction.In the terahertz frequency band,the Doppler frequency offset and the multipath effect is significant in complex indoor environments,which will reduce the orthogonality and detection accuracy of the signal.To solve this problem,the thesis proposes an integrated signal detection method based on filter banks.The polyphase filtering structure has the advantage of reducing the sampling rate when processing large amounts of highspeed data.Using it for subband filtering can also reduce the side lobe effect through the window function of the filter and improve the out-of-band attenuation speed of OFDM signals.This method avoids the excessive dependence of traditional algorithms on signal orthogonality and improves the target detection ability.The effectiveness of the algorithm is verified by simulation experiments and measured data.Traditional detection methods not only do not fully utilize the micro motion information carried in OFDM echoes,but also have a contradiction between the computational complexity and detection accuracy.The thesis proposes a parameter estimation method for micro moving targets based on joint features taking advantage of the OFDM signals with both wideband range high resolution and narrowband Doppler characteristics.This method first uses HRRP to perform a preliminary estimation of the target.Using it as a priori information of the narrowband time-frequency distribution to perform a secondary estimation of the target can reduce the amount of computation while ensuring accuracy.The thesis also proposes an instantaneous frequency estimation algorithm based on extreme path for curve extraction of multiple fretting components.Compared to peak estimation and Hough transform methods,the algorithm proposed has both advantages of extracting parameters from multiple fretting components and reducing the computational complexity,while the result is highly accurate.