AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment

For radar system tracking, a higher radar echo signal to interference and noise ratio (SINR) implies a higher tracking accuracy. However, in a countermeasures environment, increasing the transmit power of a radar may not lead to a higher SINR due to suppressive jamming. Also, the variation in the ta...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaoyou Xing, Longxiao Xu, Lvwan Nie, Xueting Li
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/10/3163
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850126171441725440
author Xiaoyou Xing
Longxiao Xu
Lvwan Nie
Xueting Li
author_facet Xiaoyou Xing
Longxiao Xu
Lvwan Nie
Xueting Li
author_sort Xiaoyou Xing
collection DOAJ
description For radar system tracking, a higher radar echo signal to interference and noise ratio (SINR) implies a higher tracking accuracy. However, in a countermeasures environment, increasing the transmit power of a radar may not lead to a higher SINR due to suppressive jamming. Also, the variation in the target radar cross-section (RCS) is an important factor affecting the SINR, since to achieve the same SINR value, a large RCS value needs less transmit power and a small RCS value needs more transmit power. Therefore, to design an efficient power allocation strategy, the influence of the electronic jamming and the target RCS need to be jointly considered. In this paper, we propose an adaptive interacting multiple power (AIMP)-based power allocation algorithm for radar network tracking by jointly considering the electronic jamming and the target RCS, achieving better anti-jamming capability and lower probability of intercept (LPI) while not reducing the tracking accuracy. Firstly, the model of the radar network tracking is established, and the power allocation problem is formulated. Next, the target RCS prediction algorithm is introduced, and the AIMP power allocation method is proposed jointly considering the electronic jamming and the impact of the target RCS. Finally, numerical simulations are performed to verify the validity and effectiveness of the proposals in this paper.
format Article
id doaj-art-d19abced82f2477285bc399707acdf8f
institution OA Journals
issn 1424-8220
language English
publishDate 2025-05-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-d19abced82f2477285bc399707acdf8f2025-08-20T02:33:58ZengMDPI AGSensors1424-82202025-05-012510316310.3390/s25103163AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures EnvironmentXiaoyou Xing0Longxiao Xu1Lvwan Nie2Xueting Li3School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, ChinaSchool of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, ChinaFor radar system tracking, a higher radar echo signal to interference and noise ratio (SINR) implies a higher tracking accuracy. However, in a countermeasures environment, increasing the transmit power of a radar may not lead to a higher SINR due to suppressive jamming. Also, the variation in the target radar cross-section (RCS) is an important factor affecting the SINR, since to achieve the same SINR value, a large RCS value needs less transmit power and a small RCS value needs more transmit power. Therefore, to design an efficient power allocation strategy, the influence of the electronic jamming and the target RCS need to be jointly considered. In this paper, we propose an adaptive interacting multiple power (AIMP)-based power allocation algorithm for radar network tracking by jointly considering the electronic jamming and the target RCS, achieving better anti-jamming capability and lower probability of intercept (LPI) while not reducing the tracking accuracy. Firstly, the model of the radar network tracking is established, and the power allocation problem is formulated. Next, the target RCS prediction algorithm is introduced, and the AIMP power allocation method is proposed jointly considering the electronic jamming and the impact of the target RCS. Finally, numerical simulations are performed to verify the validity and effectiveness of the proposals in this paper.https://www.mdpi.com/1424-8220/25/10/3163power allocationtarget RCSpulse interceptsuppressive jamming
spellingShingle Xiaoyou Xing
Longxiao Xu
Lvwan Nie
Xueting Li
AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
Sensors
power allocation
target RCS
pulse intercept
suppressive jamming
title AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
title_full AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
title_fullStr AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
title_full_unstemmed AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
title_short AIMP-Based Power Allocation for Radar Network Tracking Under Countermeasures Environment
title_sort aimp based power allocation for radar network tracking under countermeasures environment
topic power allocation
target RCS
pulse intercept
suppressive jamming
url https://www.mdpi.com/1424-8220/25/10/3163
work_keys_str_mv AT xiaoyouxing aimpbasedpowerallocationforradarnetworktrackingundercountermeasuresenvironment
AT longxiaoxu aimpbasedpowerallocationforradarnetworktrackingundercountermeasuresenvironment
AT lvwannie aimpbasedpowerallocationforradarnetworktrackingundercountermeasuresenvironment
AT xuetingli aimpbasedpowerallocationforradarnetworktrackingundercountermeasuresenvironment