低空突防用数字地形数据压缩研究

地形数据是低空突防系统最主要的信息来源之一，由于机载条件对电子设备的重量和体积有很大的限制，因此地形数据必须按低空防的要求进行压缩以减小其存储空间，本文探讨并比较了采用。ＬＰＣ，ＤＣＴ和ＢＴＣ三种压缩算法运行低空防用地形数据压缩的特点，文中首先设计了一个三阶预测器对地形数据进行ＬＰＣ压缩，其次给出了ＤＣＴ编码的恢复误差的估计式，并根据该估计式按低空防要求选取量化矩阵以压缩地形数据，最后提出了一种块间自适应的ＢＴＣ算法，仿真结果表明，块间自适应ＢＴＣ算法的综合压缩的性能较合乎低空突防的要求。

Terrain Elevation DataCompressionfor Low Altitude Penetration System

Digital terrain elevation data is one of important information for low altitude penetration system. It must be compressed to save the space of memory owing to the restriction of the weight and the volume of avionics. Three compression methods are studied and compared as follows: linear predictive coding (LPC), discrete cosine transformation (DCT) and block truncation coding (BTC). Firstly, a three order linear predictor is designed to compress terrain elevation data. Secondly, the reconstruction error of terrain elevation data compression based on DCT is estimated and quantification matrix is reasonably selected according to the equations of reconstruction error, so as to satisfy the demands of reconstruction error in low altitude penetration system. Finally, an adaptive BTC is proposed. The simulational results indicate that the adaptive BTC is better than the other two methods for low altitude penetration system.