MIMO Georadar Imaging for Depth Resolution and Coupling Removal
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Solution Overview
Problem
Existing georadar imaging methods are sensitive to antenna couplings, fail to resolve objects at different depths, and require uniform meshing, leading to masking of buried objects and high false alarm rates.
Innovation Solution
A georadar imaging method using a grid-based decomposition of the analysis spectral band into coherence sub-bands, calculating matrices of signal attenuation and phasors, estimating MIMO channels, and performing coherent and incoherent summations to generate an overall backscatter coefficient image, with OFDM signals for channel estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If migration processing is used to focus radar images, then image quality is improved, but sensitivity to antenna couplings increases
Solution Approach 1:
The patent segments the signal processing into distinct stages: raw signal acquisition, coupling removal, and then migration processing. By separating these operations, the harmful coupling effects are eliminated before they can interfere with the migration process, allowing high-quality imaging without sensitivity to antenna couplings.
Solution Approach 2:
The patent extracts and removes the coupling components from the raw radar signals before performing migration. By taking out the harmful coupling effects as a separate step, the subsequent imaging process works with cleaned signals that are not contaminated by antenna interactions.
2Area of stationary object
If uniform meshing is applied to the area of interest, then imaging coverage is improved, but processing efficiency deteriorates
Solution Approach 1:
The patent applies local quality by using uniform meshing only in regions where targets are detected, rather than applying it uniformly across the entire area of interest. This adaptive approach maintains adequate coverage in relevant areas while reducing processing burden in regions without targets.
Solution Approach 2:
The patent performs partial meshing by focusing computational resources on specific regions of interest rather than processing the entire area with uniform meshing. This partial action approach maintains necessary coverage while significantly improving processing efficiency.
3Difficulty of detecting and measuring
If deep burial objects are detected, then detection capability is improved, but false alarm rate increases
Solution Approach 1:
The patent performs preliminary coupling removal and signal cleaning before the main detection and migration processes. By preparing the signals in advance and eliminating artifacts early, the subsequent detection of deep objects is more reliable and less prone to false alarms from coupling effects.
Solution Approach 2:
The patent uses feedback mechanisms where detection results inform subsequent processing steps. By analyzing initial detection results and adjusting processing parameters accordingly, the system can distinguish true deep objects from false alarm sources, improving reliability.
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 method reduces coupling effects, resolves objects at different depths, and lowers false alarm rates, providing accurate detection and localization of buried objects.
Implementation Method 1
transmitting a radar signal into the ground by means of a transmitter antenna
Implementation Method 2
receiving the reflected signal by means of an antenna
Data Source
AI summary
A method for imaging an area of interest on the ground uses a georadar equipped with a plurality of transmitter antennas and a plurality of receiver antennas. A bistatic RCS matrix is calculated at each point of a grid based on the matrix representing the MIMO channel modelling the propagation and the reflection in the area of interest, a matrix representing the losses along the propagation paths of the channel, and a phase-shifter matrix representing the delays on these same propagation paths. The bistatic RCS matrices relating to discrete frequencies belonging to the same coherence sub-band are summed and the elements of the matrices thus obtained are then summed incoherently to provide an overall backscatter coefficient for each point of the grid. Afterwards, an image representing this backscatter coefficient at each point of the grid is generated. A method for detecting a ground target-uses the same principle.