Improved Target Localization in Multiwaveform Multiband Hybrid Multistatic Radar Networks


Temiz M., Griffiths H., Ritchie M. A.

IEEE Sensors Journal, cilt.22, sa.21, ss.20785-20796, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 21
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1109/jsen.2022.3206586
  • Dergi Adı: IEEE Sensors Journal
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.20785-20796
  • Anahtar Kelimeler: Cramér-Rao lower bounds (CRLBs), information fusion, multistatic radar, passive radar, radar waveform, target localization
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

This study proposes an algorithm to improve the target localization performance. This is implemented in a multiwaveform multiband hybrid (passive and active) multistatic radar network scenario that utilizes broadcasting signals for radar sensing in addition to the radar waveforms. Multiwaveform multiband radar receivers can exploit the broadcast signals transmitted by noncooperative transmitters, such as communication or broadcasting systems, for target sensing in addition to radar waveform. Hence, multiple measurements of the targets can be acquired and fused to improve target detection and parameter estimation. Because of utilizing various waveforms, each transmitter-receiver (Tx-Rx) pair has a different range and velocity estimation accuracy, which is also affected by the bistatic geometry of the bistatic pairs. Taking this into account, this study proposes a target localization algorithm based on bistatic Cramér-Rao lower bounds (CRLBs) for multistatic multiband radar networks. It is shown that modeling the entire network, evaluating the bistatic range CRLB of each bistatic pair in advance, and utilizing this information while estimating the target location significantly improve the localization accuracy. Moreover, the proposed algorithm also includes a target height estimation correction stage to achieve better 3-D localization accuracy.