GMTI Radar and EO Sensor Fusion via Coordinate Transformation
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Solution Overview
Problem
Current systems for fusing data from Ground Moving Target Indicator (GMTI) radars and electro-optical (EO) sensors face challenges in constructing accurate and precise tracks of ground moving targets due to measurement errors and inaccuracies, particularly in azimuthal parameters, leading to missing or incorrect assignments between radar and optical tracks.
Innovation Solution
A novel fusion system that includes a radar channel with GMTI radars and a Smooth Radar Plots (SRPs) generator, combined with an optical channel using EO sensors, which produces fused tracks by sequentially assigning GMTI plots to tracks, applying filters, and calculating locations, thereby generating Smooth Radar Plots (SRPs) for accurate tracking, and a combiner tracker that combines SRPs with EO detections to produce high-quality fused tracks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data from GMTI radars and EO sensors are fused using conventional methods, then target tracking capability is improved, but measurement errors and inaccuracies in azimuthal parameters lead to missing or incorrect assignments between radar and optical tracks
Solution Approach 1:
The patent introduces an intermediary coordinate transformation process that converts radar azimuthal measurements into optical coordinate system parameters. This intermediary transformation acts as a bridge between the radar and optical measurement systems, allowing data fusion without directly comparing inaccurate azimuthal parameters. The transformation uses known geometric relationships and sensor positions to map radar detections into the optical sensor's coordinate frame, enabling accurate track association despite individual sensor inaccuracies.
Solution Approach 2:
The patent replaces direct mechanical/geometric comparison of azimuthal parameters with a mathematical coordinate transformation system. Instead of mechanically aligning radar and optical measurements in physical space, the system uses mathematical models to transform radar detections into optical coordinates. This substitution of mechanical alignment with mathematical transformation eliminates the direct impact of azimuthal measurement errors on track assignment accuracy.
2Productivity
If conventional track fusion methods are used, then some target tracking is achieved, but constant errors in radar measurements cannot be corrected in real-time
Solution Approach 1:
The patent implements a feedback mechanism where the coordinate transformation process continuously uses updated information about sensor positions, target positions, and measurement uncertainties to refine the transformation parameters in real-time. The system feeds back the transformed coordinates and associated error estimates into the track fusion process, allowing constant errors to be identified and corrected through iterative refinement of the transformation model based on actual measurement performance.
Solution Approach 2:
The patent performs preliminary coordinate transformation and error characterization before the actual track association process. By pre-transforming radar measurements into optical coordinates and pre-characterizing the error structures, the system prepares corrected data in advance, allowing the main fusion algorithm to operate on already-corrected measurements rather than raw erroneous data.
3Speed
If direct radar and optical track assignment is performed, then processing speed is maintained, but measurement inaccuracies cause incorrect track associations
Solution Approach 1:
The patent performs preliminary coordinate transformation of radar measurements into optical sensor coordinates before the track association process. This pre-transformation step prepares the data in the correct coordinate system, eliminating the need for complex real-time coordinate comparisons during association. The preliminary action of transforming coordinates and characterizing errors beforehand allows the main association algorithm to operate quickly on pre-processed, coordinate-aligned data without sacrificing accuracy.
Data Source
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AI summary
A fusion system and method for constructing tracks of a ground target from radar and optical detections are described. The system includes a radar channel and an optical channel. The radar channel includes a Ground Moving Target Indicator (GMTI) radars providing GMTI detections in the form of GMTI plots, a GMTI tracker configured for constructing GMTI tracks of the ground target from the GMTI plots, and a Smooth Radar Plots generator configured for sequentially in time producing smooth radar plots in the form of locations of ground target on the GMTI tracks and corresponding location errors. The optical channel includes electro optical (EO) sensors sequentially in time providing EO detections in the form of coordinates of the ground target, and a combiner tracker configured for combining data streams of the radar channel with data streams of the optical channel, and producing fused tracks of the ground target.