Iterative Block Subdivision for Passive TOA TDOA Location
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Solution Overview
Problem
Current passive location methods in TOA and TDOA modes face challenges in accurately determining target locations due to measurement uncertainties, requiring extensive computational resources and failing to finely restore uncertainty areas associated with measurement errors.
Innovation Solution
A method involving successive subdivision of the initial search space into blocks, with iterative refinement and selection of candidate blocks, allowing for targeted search within regions likely to contain the target, using ad-hoc criteria to determine the presence of points within the location area, thereby achieving the desired resolution without the need for extensive space meshing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If grid methods are used to search for location areas, then the search space is systematically covered, but the computational complexity increases significantly
Solution Approach 1:
The patent divides the search space into a hierarchical structure of blocks and sub-blocks. Instead of uniformly processing the entire space, the method segments it into manageable units that can be processed iteratively. Each block is subdivided into smaller sub-blocks only when necessary, based on whether they contain points satisfying the location criterion, thus reducing overall computational complexity while maintaining location accuracy.
Solution Approach 2:
The patent applies different processing intensities to different regions of the search space. Blocks containing points that satisfy the location criterion are subdivided and processed with higher intensity, while blocks without such points are discarded. This local quality approach ensures that computational resources are concentrated on regions of interest, improving location accuracy without uniformly increasing complexity across the entire space.
2Measurement precision
If the entire space is finely meshed to achieve desired resolution, then location precision is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary filtering by checking whether blocks contain points satisfying the location criterion before conducting detailed processing. This preliminary action discards irrelevant blocks early in the process, preventing unnecessary fine meshing of the entire space. As a result, location precision is achieved in regions of interest without the time penalty of processing the entire space at full resolution.
Solution Approach 2:
The patent applies fine meshing and detailed processing only partially, specifically to blocks that contain points satisfying the location criterion. Rather than excessively processing the entire space, the method concentrates computational effort on relevant regions. This partial action approach achieves the desired location precision while significantly reducing processing time compared to uniform fine meshing.
3Measurement precision
If algebraic methods of least-square type are used, then location estimation is obtained, but the complexity increases with the number of information sources
Solution Approach 1:
The patent segments the location estimation problem into independent block-level decisions. Instead of applying complex algebraic least-square methods to all information sources simultaneously, the method divides the space into blocks and makes local decisions about which blocks to process further. This segmentation reduces implementation complexity while maintaining estimation accuracy by focusing computational resources on relevant regions.
Solution Approach 2:
The patent applies full processing effort only partially, specifically to blocks containing points satisfying the location criterion. For blocks without such points, no complex algebraic processing is performed. This partial action approach reduces implementation complexity as the number of information sources increases, while still achieving accurate location estimation in relevant regions.
Data Source
AI summary
The present invention addresses the resolving of the problems associated with the passive location of targets in TOA (Time of Arrival) or TDOA (Time Difference of Arrivals) mode. The method of passively locating a target in TOA or TDOA mode implements a meshing (subdivision) into blocks of the space in which the location area is situated. The set of the blocks that form this mesh is analyzed iteratively. On each iteration, each block of interest is subdivided into smaller identical subblocks. A block of interest is, according to the invention, a block including at least one point belonging to the location area being sought for which the shape is to be determined. The iterative process is stopped when the size of the subblocks obtained on the current iteration corresponds to the desired resolution. The invention applies in particular to the 2D or 3D location systems that include TOA and TDOA modes or mixed modes.