Target Detection Based on Canonical Correlation Technique for Large Array MIMO Radar in Spatially Correlated Noise

A novel target detection algorithm for large array multi-input multi-output (MIMO) radar in spatially correlated noise is proposed in this paper based on canonical correlation technique (CCT). In the signal model, two separate sub-arrays are employed as the receiving array of a transmit diversity MIMO radar system. Assume that the elementary noise in each sub-array has spatial correlation, and the number of receiving elements is large and grows as the same rate with the snapshots. The detection statistics is constructed based on the generalized likelihood ratio test (GLRT) criterion and canonical correlation factors between two sub-arrays, and the expression of decision threshold is derived via the second distribution of Tracy-Widom law in random matrix theory. The simulation results show that the detection performance of the proposed algorithm is better than that of the conventional condition number (CN)-based algorithm in the presence of spatially correlated noise and large array.