Optimization of Surveillance Placement in Rocket Debris Drop zone Based on Weight System and Improved NSGA-III

The monitoring and timely detection of rocket debris drop are critical challenges in space launch missions, particularly when the debris guidance system malfunctions. Existing telemetry and tracking equipment are limited by distance and line-of-sight constraints, making it difficult to capture impact events. To address this issue, we propose an observation methodology for rocket debris drop zone and optimizes its deployment strategy. A distance decay-based weight system has been formulated to characterize spatial significance, followed by the establishment of a multi objective optimization model that simultaneously minimizes deployment costs, camera quantity, and maximizes weighted coverage performance. Subsequently, the Non-dominated Sorting Genetic Algorithm (NSGA-III) has been enhanced through adaptive dynamic adjustment strategies and repair operators. Finally, deployment optimization experiment was conducted on simulated scenarios. Results indicate that the improved NSGA-III demonstrates superior convergence performance, effectively escaping local optima and enhancing search efficiency while maintaining Pareto front diversity. The proposed model and methodology provide a scientifically rigorous foundation for rocket debris drop zone monitoring system design.