基于SDLST算法的导弹状态数据压缩方法

Missile State Data Compression Method Based on SDLST Algorithm

针对海量状态数据的压缩,对旋转门趋势(Swinging Door Trending,SDT)算法进行改进,提出一种旋转门最小二乘趋势(Swinging Door Least Square Trending,SDLST)算法。通过最小二乘拟合的引入,避免了压缩偏移量对压缩精度的影响,有效控制压缩失真度在0.5以下,同时不增加算法复杂度,运算速度快,对系统资源占用少。该算法在导弹状态监测系统软件中测试完成,对导弹全寿命维护监测产生的海量状态数据,如温湿度、振动、位置姿态等进行了有效的压缩存储。验证了其有效性,具有很高的实用价值。

To compress massive data of state, we improve the Swinging Door Trend algorithm, then propose the Swinging Door Least Squares Trend algorithm. Through the introduction of the least squares fitting, the new algorithm avoids compression offset＇s impact on the compression accuracy, and reduces the compression distortion under 0. 5. The software testing in the missile status monitoring system is complete. The result verifiesd the SDLST algorithm＇s validity. It has a high practical value.