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Target localization for bistatic MIMO radar in unknown correlated noise

In this paper, target localization for bistatic MIMO radar in unknown spatially correlated noise is investigated. In our model, both the transmitter and receiver arrays are divided into two subarrays. A novel target localization algorithm is proposed by jointly estimating the directions-of-departure (DODs) and directions-of-arrival (DOAs) for transmitter and receiver subarrays in unknown noise. The algorithm exploits the canonical correlation decomposition (CCD) and the joint estimation technology based on the shift-invariance properties of different subarrays obtaining the automatic pairing. In addition, the compact formulas of stochastic Cramer-Rao bounds (CRB's) for DOD and DOA estimation are derived. The simulations show that our method effectively improves the performance of estimation by eliminating the unknown correlated noise.