Data rate management and real time operation: Recursive adaptive frame integration of limited data - art. no. 62940B

被引:0
作者
Rafailov, Michael K. [1 ]
机构
[1] Booz Allen Hamilton, Arlington, VA 22203 USA
来源
Infrared and Photoelectronic Imagers and Detector Devices II | 2006年 / 6294卷
关键词
accurate target detection; multiple thresholds; SNR; TNR; frame integration; CFAR; parallel processing;
D O I
10.1117/12.674495
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Recursive Limited Frame Integration was proposed as a way to improve frame integration performance and mitigate issues related to high data rate needed to support conventional frame integration. The technique uses two thresholds one tuned for optimum probability of detection, the other to manage required false alarm rate, and places integration process between those thresholds. This configuration allows a non-linear integration process that, along with Signal-to-Noise Ratio (SNR) gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability. However, Recursive Frame Integration Limited may have performance issues when single-frame SNR is really low. Recursive Adaptive Limited Frame Integration was proposed as a means to improve limited integration performance with really low single-frame SNR. It combines the benefits of nonlinear recursive limited frame integration and adaptive thresholds with a kind of conventional frame integration. Adding the third threshold may help in managing real time operations. In the paper the Recursive Frame Integration is presented in form of multiple parallel recursive integration. Such an approach can help not only in data rate management but in mitigation of low single frame SNR issue for Recursive Integration as well as in real time operations with frame integration.
引用
收藏
页码:B2940 / B2940
页数:10
相关论文
共 13 条
[1]  
[Anonymous], 1973, Temperature Regulation
[2]  
BAKER TL, 2002, Patent No. 20020084414
[3]  
BORNATO P, 1998, IEEE T BIOMED ENG, V45, P287
[4]  
CAULFIELD JK, 2005, P SPIE, V6206
[5]  
CUFFEL RF, 1995, P SOC PHOTO-OPT INS, V2484, P402, DOI 10.1117/12.213033
[6]  
LANGARI R, 1993, IEEE INT C FUZZY SYS
[7]  
Lanyi Xu, 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513), P357, DOI 10.1109/CCECE.2004.1345029
[8]  
PAPOULIS A, 1984, SIGNAL PROCESSING
[9]  
Papoulis A., 1991, PROBABILITY RANDOM V
[10]  
RAFAILOV MK, 2001, INFRARED TECHNOLOGY, V17