基于缓存结构的民机实时QAR数据译码方法

Decoding the Real Time QAR data with Cached Configuration Structure

摘要:

新一代通信技术的发展使得QAR数据可在飞行中实时传输。传统译码研究均针对航后QAR数据，难以高效处理实时数据。为提升实时QAR数据的译码效率，提出了基于缓存结构的译码方法，将传统的译码表转换为专门的数据结构，并进行缓存，避免了译码过程中对配置表的全表搜索，提升了译码效率；采用Go语言、Redis缓存、Influxdb2数据库，搭建了实时QAR数据译码平台；采用基于ATG网络的实测QAR数据，对译码平台的性能进行了仿真测试。针对实时QAR数据，平均译码延迟约为5ms，测试结果表明基于缓存结构的译码方法能够高效处理实时QAR数据。

Abstract:

The new generation of communication technologies enable real-time transmission of QAR data in flight. Traditional decoding researches focus on post-flight QAR data, and they are difficult to efficiently process real-time data. In order to improve the decoding efficiency of real-time QAR data, a decoding method based on a cache structure is proposed. The traditional decoding table is converted into a special data structure and cached, which avoids the full table search of the configuration table during the decoding process, improving the decoding efficiency; the Go language, Redis cache, and Influxdb2 database are adopted to build a real-time QAR data decoding platform; using the measured QAR data transmitted by the ATG network, the performance of the decoding platform was simulated and tested. For real-time QAR data, the average decoding delay is about 5ms, and the test results show that the decoding method based on the cached structure can efficiently process real-time QAR data.