The effectiveness of the PORSS algorithm was further evaluated by benchmarking it against a greedy search method which served as the baseline for comparison. In the greedy search approach, the best current row is iteratively chosen based on a continually updated detection matrix. This matrix evolves by excluding previously selected rows and any columns containing at least a value of one across these rows. As depicted in Figure , the solutions derived from the PORSS algorithm represented by the blue lines consistently outperform those obtained through the greedy search method represented by orange lines for both lowand high-end sensors. Notably, for the single-sensor (best-1) configuration, the solution identified by the greedy search is considered the ground truth, which PORSS successfully matched. This outcome underscores the PORSS algorithm's ability to find optimal solutions.