Two-dimensional Determination of the Decision Boundary for a Radar Detection Method in the Moment Space

Abstract

The radar detection with decision making in the moments space (DRACEC method) is based on a statistical analysis to determine the boundary between the background (absent target) and the anomaly (present target) classes. In this article, the boundary is taken as an ellipse and is calculated for two dimensions, emphasizing its geometric interpretation. The procedures to establish the shape, location, and size of the ellipse are highlighted, guaranteeing the probability of false alarm by applying the Neyman-Pearson criterion. The proposal establishes a methodology for calculation of the boundary when it is required to use the moments directly as a sufficient decision statistic.

Selection of Sampling Interval and Size of Random Sample for Radar Detection in the Moments Space

“…Note from Table 1 that the SCRs of the anomalies are low, however their patterns are substantially apart from those of the background. This fact manifests the detection potential of the moments space, which is demonstrated in previous works [14,17].…”

“…The above discussion arises two worthy questions: what sampling interval guarantees that the samples are decorrelated and what would be the random sample size required to obtain Gaussian moments? Works related to detection through moments can be found in [9,[12][13][14][15][16][17] but none of them has carried out a study with real radar signals to answer the above mentioned questions. Therefore, the objective of this research is to select suitable values for the sampling interval and the size of random sample to guarantee that the joint distribution of the moments is close to the Gaussian.…”