EconPapers    
Economics at your fingertips  
 

Track-Before-Detect for Dim Targets

Weihua Wu, Hemin Sun, Mao Zheng and Weiping Huang
Additional contact information
Weihua Wu: Air Force Early Warning Academy
Hemin Sun: Air Force Early Warning Academy
Mao Zheng: Air Force Early Warning Academy
Weiping Huang: Air Force Early Warning Academy

Chapter Chapter 10 in Target Tracking with Random Finite Sets, 2023, pp 283-296 from Springer

Abstract: Abstract Track-before-detect (TBD) is an effective technique used for detection and tracking of dim targets. This technique does not claim the detection result regarding the presence or absence of a target based on the single-frame data. Instead, it firstly tracks a target according to hypothetical potential paths in the multi-frame data, filters clutters and constantly accumulates the target energy based on different characteristics of target echo, clutter and noise, and estimates the target trajectory at the time of target detection. Since the TBD sets no threshold or merely sets a lower threshold for the single-frame data, information of dim targets is retained as much as possible, thus avoiding the target loss problem faced by the traditional detect-before-track (DBT) method. From the perspective of the energy utilization, the TBD integrates detection and tracking. In this way, both single scanning pulse train coherent integration and inter-scanning non-coherent integration are used to improve the energy utilization efficiency. Therefore, the TBD is able to improve the capability of radar to detect dim and small targets.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-19-9815-7_10

Ordering information: This item can be ordered from
http://www.springer.com/9789811998157

DOI: 10.1007/978-981-19-9815-7_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-07-12
Handle: RePEc:spr:sprchp:978-981-19-9815-7_10