Over‐the‐horizon radar target registration improvement by terrain feature localization

Abstract

Abstract. This paper addresses the problem of over-the-horizon radar (OTHR) target position registration in the presence of ill-defined ionospheric structures. At present, OTHR is subject to frequent position uncertainties due to ionospheric abnormalities, such as tilts and ambiguous multipath propagation modes, that are difficult to model adequately during radar operation. The detection and registration of discrete terrain features in parallel with routine radar operations were studied with the goal of significantly reducing radar target position errors under most circumstances. The Wide Aperture Research Facility (WARF) experimental OTH radar testbed was modified to enable the automatic detection, processing, display, and registration of terrain features and HF repeater (beacon) echoes in parallel with aircraft detection and tracking operations. Many distinct terrain feature locations were studied in significant detail, including cities, mountain peaks, and an island, and the automatically determined position correction offsets were statistically compared with collocated beacons that served as ground truth. It was found that 100% of the offsets had expected errors of less than 5.7 nautical miles (1 nautical mile equals 1.852 km); and 93% of the offsets (with better ionospheric propagation) had expected errors of less than 3.2 nautical miles. We conclude from the research that terrain features can be used to provide coordinate registration benchmarks over an OTHR coverage area in the same way that beacons can be used.

An Improved Coordinate Registration for Over-the-Horizon Radar Using Reference Sources

“…This procedure is out of the scope of this paper. The reader is referred to [24][25][26]. In other words, we assume that the pair (y l , z l ) of a reference source and its corresponding OTHR measurement is known.…”

“…One way to tackle the problem above is using reference sources. The reference sources may include HF beacons or transponders [23,24], terrain features (e.g., coastlines, islands and mountains) [25][26][27][28][29], microwave radars [30], and the position information of cooperating targets, such as airliners equipped with automatic dependent surveillancebroadcast (ADS-B) and ships equipped with automatic identification system (AIS). While using the reference sources in CR, their locations in the ground coordinates are assumed to be known.…”

“…For example, Weijers et al [24] described the CR experiments using HF beacons around the US east coast, which demonstrated that using beacons can significantly improve CR. A 3-year investigation was conducted using the Wide Aperture Research Facility experimental OTHR to determine if terrain features could be used as CR benchmarks [25], the results of which showed that terrain features could be used in the same way with beacons. In these work, correction factors are obtained by comparing the OTHR measurements of the reference sources with their locations in ground coordinates, which are used to correct the location of the targets of interest surrounding to the reference sources.…”

Reference source‐aided coordinate registration method for over‐the‐horizon radar using ensemble learning

“…For example, Weijers et al [16] described CR experiments using HF beacons around the US east coast, which demonstrated that using beacons can significantly improve CR. A 3-year investigation was conducted using the Wide Aperture Research Facility experimental OTHR to determine if terrain features could be used as CR benchmarks [17]. The results showed that terrain features could be used in the same way as beacons.…”

SVM Based Land/Sea Clutter Classification Algorithm

“…The received radar echo is severely affected by the ionosphere, so how to form effective features is of crucial important [7]. Furthermore, there are not a definite classification boundary between amplitudes of land/sea clutter in regions with complex topography and geomorphology.…”