Decentralized Target Tracking Using Cubature and H-Infinity Filters

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current tracking systems for moving targets with non-linear paths face accuracy issues due to linearized approximations and inefficient information sharing between surveillance platforms, leading to increased noise and tracking errors.

Innovation Solution

A decentralized system using consensus cubature and H-infinity filters for target tracking, which applies cubature information filters to sensor data, excludes outliers with H-infinity filters, and combines estimates from multiple tracking systems to reduce errors and computational resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If linearized approximations are used to predict object paths, then computational complexity is reduced, but tracking accuracy deteriorates due to overweighing noise or outlier readings

Engineering Contradiction:

Improvecomputational complexityVSAvoidtracking accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent changes the mathematical parameters from linearized approximations to non-linear cubature filters and H-infinity filters. This transformation maintains computational tractability while significantly improving tracking accuracy by properly handling non-linear motion paths and rejecting outlier readings without oversimplifying the underlying physics

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent combines multiple filtering approaches (cubature information filter and H-infinity filter) into a composite tracking system. This composite approach leverages the strengths of each filter type to achieve both computational efficiency and high tracking accuracy, resolving the contradiction between simplicity and precision

Inventive Principle:

Principle #40Composite materials

2Measurement precision

If centralized information sharing is implemented between surveillance platforms, then tracking accuracy improves, but computational time and resources increase

Engineering Contradiction:

Improvetracking accuracyVSAvoidcomputational time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the centralized tracking system into distributed autonomous nodes that each perform local cubature filtering and H-infinity filtering independently. This segmentation eliminates the need for continuous centralized computation while maintaining tracking accuracy through localized information processing and selective data sharing between platforms

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Each surveillance platform in the patent performs self-service tracking by autonomously applying cubature and H-infinity filters to its own sensor data. This self-service capability reduces dependency on centralized processing, thereby decreasing computational time and resource requirements while preserving tracking accuracy through independent error correction

Inventive Principle:

Principle #25Self-service

3Measurement precision

If centralized information sharing is implemented between surveillance platforms, then tracking accuracy improves, but system complexity and resource requirements increase

Engineering Contradiction:

Improvetracking accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent divides the complex centralized system into simpler autonomous segments that each implement standard cubature and H-infinity filtering algorithms. This segmentation reduces overall system complexity by distributing processing tasks while maintaining accuracy through consistent application of proven filtering methods at each node

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the system architecture from centralized parameter management to distributed autonomous parameter processing. Each platform independently manages its own filtering parameters and state estimates, reducing system complexity by eliminating centralized coordination overhead while maintaining tracking accuracy through standardized filter implementations

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10606266B2Tracking a target moving between states in an environment

Publication Date: 2020.03.31 THE BOEING CO

AI summary

An apparatus is provided for tracking a target moving between states using an iterative process. The apparatus receives sensor data for a current state i, and applies a cubature information filter and an H-infinity filter thereto to respectively produce an estimate for the upcoming state i+1 and a measure of error thereof, and adjust the measure of error. The apparatus then defines a consensus estimate of the upcoming state i+1 and a consensus adjusted measure of error thereof from the estimate and adjusted measure of error, and a second estimate and second adjusted measure of error that is received from at least one second apparatus tracking the target. The apparatus then applies a cubature information filter to the consensus estimate of the upcoming state i+1 and the consensus adjusted measure of error to predict the upcoming state i+1.