Research on Real-Time Fusion Technology of Range Telemetry Data

Figures & Tables

Approach	Problem	Literature number
P-FA	The problem of matching the frame data and the frame count when the frame is lost is not solved	[13]
P-FA	Large amount of calculation, not easy to promote	[19]
P-TCMA	The number of data positions is wrong when the frame is dropped	[18]
P-TCMA	Data transmission delay is not considered	[12]
P-ECA	Depends on device index value	[16]
	Frame count error has not been resolved	[10]
	No consideration of transmission delay	[4]
	Large amount of calculation, not easy to promote	[3]

Approach	Problem	Literature number
PSF-QEA	Data error does not affect the frame length, causing quality misjudgment.	[18]
PSF-QEA	To solve the judgment error caused by dropped frames	[6]
PFF-QEA	Unsolved the problem of different comparison results caused by dropped frames and errors	[20]
	The assessment basis is relatively simple	[10]
	Not given due to frame loss	[3]
	Data preprocessing requirements are high, and the incomplete F-frame data is discarded, which is not conducive to the full use of data.	[5]
PSF-QEA	The calculation is cumbersome and not easy to promote	[11]
PSF-QEA	Cluster center radius is not easy to choose	[6]

Approach	Problem	Literature number
FF-QEA	The system overhead is large, and when the amount of data increases, the information is too late to process.	[14]
FF-QEA	Accurate quality evaluation when errors occur in unresolved frame counts	[8]
SF-QEA	Increased algorithm time complexity	[2]

处理方法	问题	文献编号
基于选段的事后质量评估算法	数据误码并不影响帧长度，造成质量误判。	[18]
基于选段的事后质量评估算法	为解决丢帧引起的评判失误	[6]
基于全帧的事后质量评估算法	未解决丢帧误码引起的对比结果均不相同的问题	[20]
	评估依据较为单一	[10]
	未给出丢帧引起的	[3]
	数据预处理要求较高，丢弃残缺的全帧数据，不利于数据的充分利用。	[5]
基于子帧的事后质量评估算法	计算繁琐，不易推广	[11]
基于子帧的事后质量评估算法	聚类中心半径不易选取	[6]

Frame number	GS1	GS2	Fusion result	Correct
1	28586	65530	28586	65530
2	65531	65467	65467	65531
3	65532	65356	65356	65532
4	65523	65533	65523	65533