A Kalman-based tracker exploiting spillover of target energy at the detection stage

In the present paper, we focus on the design of a Kalman-based algorithm to track a single target in range. The proposed approach exploits spillover of target energy between consecutive matched filter samples; to this end, measurements are obtained by comparing a GLRT detector computed over consecutive samples to a proper threshold. We assume that the received useful signal is known up to complex factors modeled as deterministic parameters whose relative values depend on the actual target position; moreover, we suppose that the target is embedded in white Gaussian noise with unknown power. The performance analysis is conducted in comparison to a more conventional Kalman-based tracker that interpolates consecutive samples to take advantage of the spillover. Remarkably, the proposed estimation scheme can provide accurate estimates of the target position (and the velocity as well) within the cell under test.