Moving target detection and tracking with multiplatform radar network (MRN)

IET Radar, Sonar & Navigation

卷:16

Daiyin Zhu¹  Beining Wang¹  He Yan¹  Zhe Geng¹  Jindong Zhang¹ 

[1] College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics Nanjing China;

关键词: adaptive radar countermeasures;    cognitive radar;    deep neural network;    internet of battlefield things (IoBT);    MIMO radar;    radar network;   

DOI  :  10.1049/rsn2.12222

来源: DOAJ

【 摘 要 】

Abstract A multiplatform radar network (MRN) composed of multiple transmitting and receiving facilities is advantageous over monostatic radar in moving target detection (MTD) and tracking due to the diversity gain. Within the framework of the Internet of Battlefield Things (IoBT), the authors propose that the airborne platforms equipped with the cognitive multimodal radar (CMR), the subarray‐based MIMO radar (SMR), the active electronically scanned array (AESA) radar, and the adaptive radar countermeasures (ARC) should team up in target detection and tracking. To obtain better target detection and tracking performance, the probing signals from the CMR, the SMR, and the AESA radar are adaptively optimised based on the scenario under consideration. The ARC consists of two parts: 1) RF signal sensing and recognition with deep neural network (DNN), that is, to detect, identify, and localise multiple radio frequency emitters; 2) intelligent fake return creation and jamming to confuse the enemy radars in real time in the field. This work aims to serve as a good reference for future researchers interested in developing MRN with diverse nodes and the general teaming of radars on the battlefield.

【 授权许可】

Unknown