MIMO Radar Signal Model for Waveform Separation Residuals
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Solution Overview
Problem
Current MIMO radar systems face inefficiencies in detecting moving objects due to the assumption of perfect waveform separation, which is difficult to achieve across all Doppler frequencies and time delays, leading to waveform separation residuals that affect detection accuracy.
Innovation Solution
The proposed MIMO radar system incorporates an explicit signal model that accounts for imperfect waveform separation residuals, using orthogonal codes to minimize interference and a spatial MIMO detector with a baseband range-Doppler object detector to accurately detect moving objects by compensating for Doppler shifts and separating waveforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If perfect waveform separation is assumed in MIMO radar systems, then the detection process is simplified, but detection accuracy deteriorates due to unaccounted waveform separation residuals
Solution Approach 1:
The patent converts the harmful waveform separation residuals into a beneficial signal by explicitly modeling them as a structured interference component. Instead of treating residuals as pure noise to be filtered out, the system models them as predictable interference patterns that can be compensated for, thereby improving detection accuracy without significantly complicating the detection process.
Solution Approach 2:
The patent introduces an intermediary signal model that mediates between the transmitted signals and the received signals. This intermediate model explicitly accounts for waveform separation residuals, allowing the system to bridge the gap between simplified detection assumptions and accurate detection requirements.
2Measurement precision
If waveform separation residuals are accounted for in the signal model, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent changes the parameters of the signal model to explicitly include waveform separation residual terms. By modifying the signal representation to incorporate these residual components as structured interference rather than random noise, the system achieves higher detection accuracy while keeping the model complexity manageable through parameterization.
3Object-generated harmful factors
If orthogonal codes are used to minimize interference between transmitters, then mutual interference is reduced, but waveform separation residuals still occur across all Doppler frequencies and time delays
Solution Approach 1:
The patent applies partial action by using orthogonal codes to minimize interference only to the extent possible, then explicitly modeling and compensating for the remaining residuals. Rather than expecting perfect interference cancellation, the system partially uses orthogonal coding and then addresses the remaining interference through explicit residual modeling in the signal processing stage.
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
This approach enhances the accuracy of detecting moving objects by considering waveform separation residuals, improving the system's ability to distinguish between objects and background clutter, even in dynamic environments.
Implementation Method 1
This invention generally relates to a radar system used for detecting a moving object
Implementation Method 2
Each receiver of the set of receivers receives a reflected signal that is a superposition of reflections of the multiple reference signals transmitted by the multiple transmitters
Implementation Method 3
it is assumed that each receiver of the MIMO radars achieves a perfect waveform separation by applying corresponding orthogonal codes that are used at the transmitters to transmit signals
Implementation Method 4
The MIMO radars may be implemented in an automobile and may be used to detect one or more moving objects with respect to the automobile
Data Source
AI summary
A multiple input multiple output (MIMO) radar system for detecting a moving object is based on an explicit signal model. The explicit signal model accounts for waveform separation residuals by relating measurements of the virtual array to an auto-term including a Kronecker product of object-receiver signatures and transmitter-object signatures; and a cross-term including a Kronecker product of object-receiver signatures and transmitter-object residual signatures. The radar system uses a spatial MIMO object detector that is based on the explicit signal model to detect the moving object.