Multi-target detection is the main function of radar. Cognitive radar, which can adaptively investigate the radar scene and determine the next action based on previous measurements, has better performance. In this paper, a multi-target detection method and an adaptive waveform design algorithm for cognitive MIMO radar are proposed. In this method, the multi-target detection is modeled as a multi-hypothesis testing. The multi-hypothesis testing is investigated according to sequentially received data. Along with the multi-target detection method, an adaptive waveform design algorithm based on information theory is proposed to improve the efficiency of the multi-hypothesis testing. We adopt semidefinite relaxation (SDR) technique and semidefinite programming (SDP) to tackle the nonconvex design problem. Numerical examples demonstrate that the proposed multi-target detection method has better performance than classical target detection method, and the proposed adaptive waveform design algorithm can significantly improve the performance of the proposed multi-target detection method.

To distinguish/detect multiple close targets is of great significance in many areas, and the typical tool is the GLRT detection. However, there will be distinguishing difficulty and mutual interference when present targets are very close. Furthermore, it is difficult for binary decision theory to tell where the targets locate exactly as it can only make a decision that whether there is one or two targets present. As it cannot utilise the prior information of target number, it also suffers a poor detection performance. To overcome those disadvantages, the authors bring in multi‐hypothesis test (MHT) to the multi‐target model within co‐located MIMO radar. They also apply the sequential probability ratio test (SPRT) to locate the multiple range‐located targets efficiently, whose angles are known as a prior. The simulations show that authors’ SPRT‐based detection is more fast and constant comparing to the existing GLRT‐based detection taken within cell‐by‐cell.

This study addresses the challenge of cognitive waveform design for multiple-input–multiple-output (MIMO) radar systems operating in cluttered environments. It focuses on the key practical requirements for transmitting time-domain waveforms and proposes a novel approach. This method first determines the optimal frequency-domain waveform and then designs a time-domain waveform that closely approximates the frequency-domain solution. The primary objective is to enable MIMO radar systems to transmit orthogonal waveforms while accommodating various constraints. A frequency-domain waveform optimization model was initially developed using the principle of maximizing dual mutual information (DMI), and the energy spectral density (ESD) of the optimal waveform was derived using the water-filling method. Next, a time-domain waveform approximation model is constructed based on the minimum mean square error (MMSE) criterion, which incorporates constant modulus and peak-to-average power ratio (PAPR) constraints. To minimize the performance degradation of the waveform, an improved adaptive gradient descent genetic algorithm (GD-AGA) was proposed to synthesize multichannel orthogonal time-domain waveforms for MIMO radars. The simulation results demonstrate the effectiveness of the proposed model for enhancing the performance of MIMO radar. Compared with traditional genetic algorithms (GA) and two enhanced GA alternatives, the proposed algorithm achieves a lower ESD loss and better orthogonal performance.

We propose and experimentally demonstrate a noise mitigation scheme for coherent optical discrete multitone (DMT) signal transmission system. The proposed scheme can mitigate the laser phase noise and additive white Gaussian noise (AWGN) simultaneously when optical DMT signal is coherently detected. In the digital signal process (DSP), the laser phase noise is first estimated and compensated through moving average filter. The AWGN is then reduced by considering the time-domain real-valued or frequency-domain symmetrical conjugation characteristic of DMT signal. Finally, we conduct an experiment to transmit dual-polarization (DP-) DMT signal based on a low complexity coherent detection structure with only two pairs of input and output ports. The experimental results prove that the proposed scheme can enhance the signal-to-noise ratio (SNR) and effectively reduce the effect of laser phase noise even the laser linewidth is as large as 10 MHz. The DP-DMT signal is successfully transmitted over 1920-km standard single mode fiber (SSMF) in the experimental demonstration. The analysis of computational complexity also indicates that the proposed DSP scheme requires less number of complex multiplication operations and has larger laser phase noise tolerance than other DSP schemes.