Ship Radial Size Estimation in High-Resolution Maritime Surveillance Radars via Sparse Recovery Using Linear Programming

Abstract

For high-resolution maritime surveillance radars operating at scan mode and transmitting long duration pulses, radial size estimation of ships is severely interfered by range sidelobe effect of pulse compression. Due to range sidelobe effect, strong ship returns often cover a range interval wider than its radial size and the range interval covered by detected ship returns is sometimes a severe overestimate of its radial size. An approach to mitigate severe overestimation of ship radial sizes is to find the borders of high-resolution range profile (HRRP) of a ship. Therefore, ship radial size estimation boils down to the recovery of sparse HRRPs of ships from radar returns with heavy-tailed sea clutter in a coherent processing interval (CPI) only containing several pulses. In this paper, a sparse recovery method using linear programming (LP) is proposed to recover sparse HRRPs of ships from radar returns with heavy-tailed sea clutter. As a minor contribution, a full scheme is presented for ship radial size estimation in high-resolution surveillance radars operating at scan mode, which consists of coherent detection along with range cells, annotation of the range interval covered by ship returns, the decision of severe range sidelobe effect, recovery of sparse HRRPs of ships, and radial size computation. The performance of the proposed LP-based method to estimate ship radial size is evaluated by using simulated and real radar data. The experimental results show that it attains more accurate radial size estimates of ships than existing methods.

Keywords

• High-resolution maritime surveillance radars
• range sidelobe effect
• radial size estimation
• high-resolution range profile (HRRP)
• heavy-tailed sea clutter
• sparse recovery