High-Resolution Direct Position Determination Using Multiple Asynchronous Sensors

Existing direct position determination algorithms using multiple asynchronous sensors utilize the properties of the noise subspace and signal subspace to construct a multiple signal classification-like cost function. Based on this algorithm, this paper further leverages the characteristics of the signal subspace to develop a new cost function that produces sharper peaks at the target locations. Experimental results demonstrate that the proposed algorithm offers higher resolution performance in the presence of closed spaced target scenario.