Interferometric Radar Ghost Target Elimination via Evidence Grid

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Interferometric radar systems face limitations in precise target location due to phase ambiguity, leading to the presence of 'ghost' targets, and require multiple receivers or larger antennas, complicating antenna design and increasing computational complexity.

Innovation Solution

Combining Interferometric radar with an evidence grid to process detection signals from multiple spatial regions, allowing for the calculation of probability values that eliminate phase ambiguities and differentiate between true and ghost targets, thereby improving localization accuracy without increasing antenna size.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If interferometric methods with two or more receivers are used to improve target location precision, then measurement precision is improved, but device complexity increases due to multiple antennas and receivers

Engineering Contradiction:
Improvetarget location precisionVSAvoidantenna design complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the spatial region into an evidence grid with multiple cells, where each cell represents a discrete location. This segmentation allows the system to process phase ambiguity information from multiple spatial divisions rather than requiring multiple physical receivers, thereby reducing device complexity while maintaining measurement precision through computational differentiation of true targets from ghost targets across the grid cells

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces an evidence grid as an intermediary computational structure between the interferometric receivers and the target location determination. This evidence grid mediates the processing of phase difference measurements by organizing potential target locations into discrete cells, allowing the system to resolve phase ambiguities through probabilistic reasoning across the grid rather than requiring additional physical receivers

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If receiver separation distance is increased to improve target localization accuracy, then measurement precision is improved, but the number of ghost targets increases

Engineering Contradiction:
Improvetarget localization accuracyVSAvoidnumber of ghost targets
Core Design Contradiction:
Measurement precisionVSObject-generated harmful factors

Solution Approach 1:

The patent applies feedback by using multiple radar returns and iteratively updating the evidence grid based on accumulated measurements. Each new measurement provides feedback that helps distinguish true targets from ghost targets through probabilistic updating of cell occupancies, allowing the system to maintain high localization accuracy while suppressing ghost target generation even with increased receiver separation

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent performs preliminary action by pre-defining the evidence grid structure and occupancy states before target identification is complete. This preliminary organization of spatial cells allows the system to proactively manage and differentiate between potential true targets and ghost targets throughout the measurement process, rather than dealing with ambiguities after detection

Inventive Principle:
Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The evidence grid effectively eliminates ghost targets and enhances the resolution of target localization, achieving superior performance with fewer antennas compared to traditional Interferometric methods, while maintaining precision equivalent to larger single-antenna systems.

Implementation Method 1

a radar transmits a first detection signal over a first spatial region and a second detection signal over a second spatial region

Methodology Applied
Scientific EffectElectromagnetic radiation: Electromagnetic Induction

Implementation Method 2

the ability of a radar to precisely locate a target is limited by the beamwidth of the radar, since a radar return can come from anywhere in the cone formed by the beam

Methodology Applied
Scientific EffectRadar reflection: Reflection

Implementation Method 3

by comparing the differences in phase between the received signals, it is possible to obtain a much more accurate location of a target than with a single receiver. Because the phase can be measured only modulo 2π, the location of the target cannot be determined uniquely because of phase ambiguity

Methodology Applied
Scientific EffectPhase difference measurement: Interference

Data Source

PatentEP2397866B1Systems and methods for using an evidence grid to eliminate ambiguities in an interferometric radar
Publication Date: 2017.09.13 HONEYWELL INTERNATIONAL INC
  • EP2397866B1 patent drawingFigure 1
  • EP2397866B1 patent drawingFigure 2
  • EP2397866B1 patent drawingFigure 3

AI summary

A system (100) includes an Interferometric radar (102) that transmits a first detection signal over a first spatial region and a second detection signal over a second spatial region. The second region has a first sub-region in common with the first region. The system further includes a processing device (104) that assigns a first occupancy value to a first cell in an evidence grid. The first cell represents the first sub-region, and the first occupancy value characterizes whether an object has been detected by the first detection signal as being present in the first sub-region. The processing device calculates, based on the first and second detection signals, the probability that the first occupancy value accurately characterizes the presence of the object in the first sub-region, and generates a data representation of the first sub-region based on the probability calculation.