Tensor model built from vector for Angle and Doppler frequency estimation with Expanded Nested Spatial-Temporal Sampling

In this paper, the transmit-receive array and delay receive stage of MIMO radar are configured in an expanded nested mode to enhance the estimation of parameters. Initially, the transmit-receive array of MIMO radar is set up as an expanded nested array, and the time intervals for the delay receivers are similarly patterned. Subsequently, we obtain and vectorize the covariance matrix of the received signals to expand the degrees of freedom (DOF) in both the time and spatial domains. After eliminating redundant spatial-temporal DOFs, we directly construct a tensor on the basis of the new single snapshot signals and employ tensor decomposition techniques to extract the angle and Doppler parameters of targets. Compared to traditional methods, this approach reduces the computational burden of solving for the pseudo-covariance matrix by directly constructing tensors from vectors. Additionally, this method also expands the DOF in the time and spatial domains, significantly enhancing the precision of parameter estimation. A series of simulation experiments validate the effectiveness of the algorithm.