Research on sea clutter model of emulating aircraft motion based on shore-based multichannel radar

• Published in: International journal of remote sensing Vol. 43; no. 6; pp. 2227 - 2243
• Main Authors: Wan, Jintong, Luo, Feng, Zhang, Yushi, Xu, Xinyu, Yin, Yalei
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 19.03.2022; Taylor & Francis Ltd
• Subjects: Airborne radar; Airborne remote sensing; Aircraft; aircraft motion emulation; Antenna arrays; Antennas; Clutter; cost effectiveness; Coupling; Eigenvalues; Modelling; Movement; multichannel; Radar; Radar data; sea clutter; Sea state; Sea states; Simulation; space and time; Space-time adaptive processing; Spacetime; Surface clutter; Width
• ISSN: 0143-1161; 1366-5901; 1366-5901
• DOI: 10.1080/01431161.2022.2058892

Space-time adaptive processing (STAP) is an important clutter suppression technique in airborne multichannel radar. It can be a challenging problem to apply STAP to the maritime airborne radar without knowledge of sea clutter space-time coupling characteristics. The radar sea clutter data with space-time coupling characteristics can be obtained by airborne multichannel radar, but the flight testing is very expensive. A cost-effective technique is presented for emulating airborne motion based on shore-based multichannel radar. The technique is implemented by the same array shared with transmit and receive antenna, where the transmit array uses an inverse displaced phase centre antenna to emulate platform motion and the receive array is used for receiving data. Based on the above technique, a sea clutter model of aircraft motion emulation is proposed. Then, we verify the model by quantitatively comparing the number of eigenvalue and the spread width of the space-time power spectrum between the simulated and measured data. The result shows that the eigenvalue number and the spread width of 3 dB clutter ridge of measured data are more than 79.5% of that belonging to simulated data. It means that the simulated radar sea clutter data generated by this model can better fit the measured data under sea states classes 1-4, which can provide support for the analysis of sea clutter space-time characteristics.