基于机器学习的火箭残骸定位研究
Research on the Positioning of Rocket Debris Based on Machine Learning

在现代航天领域，火箭发射后的残骸定位至关重要，准确定位是安全回收的关键。本研究针对火箭残骸的准确定位展开研究，提出了一种利用监测设备接收音爆信号的定位方法，以实现对残骸位置和时间的精确掌控。针对问题一，我们为单个残骸的定位建立了模型，分析了监测设备接收到的音爆信号的时间和位置信息，确定了精准定位残骸所需的最低监测设备数量。通过数学建模和求解，我们得出了定位的最小设备需求。针对问题二，考虑到可能同时出现多个残骸的音爆信号，我们开发了识别各个残骸音爆信号的方法，能够根据不同音爆信号的特征，确定每个残骸的准确位置和时间，实现多个残骸的精确定位。针对问题三，我们利用修正模型，从实际监测数据中筛选出合适的数据，进一步确定多个残骸空中音爆时的位置和时间。经过数据验证，证明了模型的有效性，为实际应用提供了可靠的依据。针对问题四，我们考虑到监测设备的记录时间可能存在随机误差，因此提出了一个修正模型的方法，通过数据修正和分析降低误差，并提供解决方案以应对难以避免的时间误差，从而提升了残骸定位的准确性和可靠性。综上所述，本研究提出了一种基于监测设备接收音爆信号的火箭残骸定位方法，通过数学建模和实际数据分析，实现了残骸位置和时间的精确定位，为火箭残骸的安全回收和后续分析提供了技术支持。
In the field of modern aerospace, the positioning of debris after rocket launch is crucial, and accurate positioning is the key to safe recovery. This study focuses on the accurate positioning of rocket debris and proposes a positioning method that uses monitoring equipment to receive sonic boom signals to achieve accurate control of the location and time of the debris. For problem one, we established a model for the positioning of a single debris, analyzed the time and location information of the sonic boom signal received by the monitoring equipment, and determined the minimum number of monitoring equipment required for accurate positioning of the debris. Through mathematical modeling and solution, we obtained the minimum equipment requirements for positioning. For problem two, considering that the sonic boom signals of multiple debris may appear at the same time, we developed a method to identify the sonic boom signals of each debris, which can determine the exact location and time of each debris according to the characteristics of different sonic boom signals, and achieve accurate positioning of multiple debris. For problem three, we used the modified model to filter out appropriate data from the actual monitoring data and further determine the location and time of multiple debris during the sonic boom in the air. After data verification, the effectiveness of the model was proved, providing a reliable basis for practical application. Regarding question 4, we considered that the recording time of the monitoring equipment may have random errors, so we proposed a correction model method to reduce the error through data correction and analysis and provide solutions to deal with the inevitable time error, thereby improving the accuracy and reliability of debris positioning. In summary, this study proposed a method for locating rocket