Range estimation using adjacent matched filter samples

By jointly considering multiple adjacent matched filter samples, target localization can be more accurate than considering only a single sample. For sub-bin range estimation, a power-weighted centroid is typically the method of choice due to its simplicity. However, centroiding does not consider the correlation between adjacent samples, and is hence sub-optimal. By making assumptions on the structure of the transmitted pulse, a closed-form maximum likelihood estimator (MLE) for range can be found. The derived MLE is compared to centroiding using mean squared error (MSE) as the performance metric. Numerical simulations show that the MLE outperforms centroiding in all practical cases. Detection threshold values based on observed signal-to-noise ratio are provided for several practical false alarm probabilities.