Name
Title | ||
|---|---|---|
Accurate Estimation the Scanning Cycle of the Reconnaissance Radar Based on a Single Unmanned Aerial Vehicle. |
Abstract | ||
|---|---|---|
In modern warfare, as a long distance detection equipment, a reconnaissance radar is crucial to monitor the sensitive regions and the intelligence of airborne targets. It is important for the opponent to identify the tactical information about the enemy's reconnaissance radar. It has a great influence on the war. Scanning cycle of the monitoring radar is an important parameter for the counterreconnaissance of the hostile radar source in the electronic countermeasure. Since the pulse Doppler (PD) radar is one of the most widely used type in modern reconnaissance radar domains, this paper focuses on scanning cycle estimation of the reconnaissance radar (PD radar) using a single unmanned aerial vehicle (UAV). We propose an effective method to reconstruct the main-beam pattern (MBP) curve of the radar antenna based on the norm approximation algorithm, and then the reconstructed MBP curve of the radar antenna is exploited to estimate the scanning cycle of the reconnaissance radar. By hovering the UAV at the same place, the scanning cycle of the reconnaissance radar can be estimated according to the reconstructed MBP curve. In the simulation section, we check the validity and robustness of the proposed method through the performance comparison with the Cramer-Rao lower bound. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ACCESS.2017.2762742 | IEEE ACCESS |
Keywords | Field | DocType |
Reconnaissance radar,scanning cycle,unmanned aerial vehicle (UAV),main-beam pattern (MBP),norm approximation | Radar engineering details,Continuous-wave radar,Computer science,Remote sensing,Man-portable radar,Artificial intelligence,Radar lock-on,3D radar,Fire-control radar,Distributed computing,Computer vision,Radar imaging,Bistatic radar | Journal |
Volume | ISSN | Citations |
5 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pengwu Wan | 1 | 0 | 2.37 |
| Benjian Hao | 2 | 101 | 12.30 |
| Zan Li | 3 | 809 | 100.82 |
| Xiao Ma | 4 | 487 | 64.77 |
| Yue Zhao | 5 | 58 | 28.59 |