Abstract
The article describes an innovative algorithm of a radar north correction estimation. The uniqueness of the algorithm is the pure data/software nature without need for any additional north-seeking equipment. This procedure is a key step of a registration local coordinate system to a global one. The presented method is an application of cognitive radar approach, matching of radar ground clutter echoes with a-priori information, vector map data, and terrain elevation profile. The algorithm is based on matching observed ground clutter areas within received radar signal, with (corresponding) areas visible upon terrain profile data. The designed north correction algorithm was tested on real radar signal recorded on the 2D surveillance short-range radar ReVISOR made by RETIA, a.s. The current implementation utilizes SRTM height profile data.
Highlights
A radar system is usually used to perform surveillance or tracking of surface, airborne or space targets
The article describes a software-based north correction estimation method based on alignment of surveillance radar ground clutter echoes with visible parts of terrain
The algorithm can be implemented in any programming language supporting double precision of float point numbers
Summary
A radar system is usually used to perform surveillance or tracking of surface, airborne or space targets. Measurement of local coordinate system altitude alignment relative to the global one is more challenging Mutual attitude of these coordinate systems can be expressed by the set of three angles: Roll, Pitch and Yaw. Ground based radar systems are usually operated in the leveled position. The article describes a software-based north correction estimation method based on alignment of surveillance radar (with rotating antenna) ground clutter echoes with visible parts of terrain. North correction is estimated directly in the radar local coordinate system and no further calibration is needed during radar production (in comparison with other methods). THE ROUGH NORTH-SEEKER CORRECTION ALGORITHM PRINCIPLE A received radar signal consists of target echoes, various types of clutter, and noise. The yaw bias north correction estimator is based on mutual correlation of the clutter visibility model with the ground clutter signal. The outputs from both branches are processed by cyclic correlation and used for northcorrection estimation
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