Radar Target Detection Using Strong Reflection Retrieval
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Solution Overview
Problem
Existing radar apparatuses face challenges in accurately detecting targets due to interference from strong reflection objects, such as large vehicles, which complicates the detection of leading cars in vehicle following systems.
Innovation Solution
A radar apparatus with a retrieval unit, estimation unit, and determination unit that identifies strong reflection objects, estimates their orientation, calculates signal power using frequency components, and determines target presence based on power thresholds, employing methods like Capon and ESPRIT to enhance detection precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional beam scanning or null scanning methods are used for arrival direction estimation, then the radar apparatus can detect targets in general conditions, but false detection easily occurs when strong reflection objects exist around the target
Solution Approach 1:
The patent segments the detection process into three distinct stages: (1) retrieving strong reflection objects based on signal strength thresholds, (2) estimating orientations around these strong reflection objects, and (3) calculating power and determining target presence in those specific orientations. This segmentation allows the system to handle strong reflection objects and potential targets separately, preventing false detections while maintaining detection accuracy.
Solution Approach 2:
The patent performs preliminary retrieval of strong reflection objects before conducting the main target detection process. By identifying and isolating strong reflection objects first, the system can then focus its detection efforts on orientations around these objects, performing the necessary calculations only in relevant directions rather than scanning all orientations, thus improving both accuracy and efficiency.
2Measurement precision
If the radar apparatus scans all orientations to detect targets, then it can detect targets in any direction, but the detection precision decreases when strong reflection objects interfere with the signal
Solution Approach 1:
The patent applies local quality by concentrating the arrival direction estimation and power calculation operations specifically around the orientations of strong reflection objects, rather than uniformly across all orientations. This localized approach allows the system to achieve high precision in critical areas where targets are most likely to be missed or falsely detected, while reducing computational burden in less critical directions.
3Measurement precision
If conventional target detection methods are used, then the system operates with simple processing, but it cannot distinguish targets from strong reflection objects in challenging environments
Solution Approach 1:
The patent performs preliminary retrieval of strong reflection objects using signal strength thresholds before conducting detailed orientation estimation and power calculation. This preliminary action separates the detection process into manageable stages, allowing the system to handle complex multi-object scenarios systematically without overwhelming computational requirements at any single stage.
Solution Approach 2:
The patent transitions from conventional single-dimension signal strength-based detection to a multi-dimensional approach by introducing orientation as an additional dimension. By estimating orientations around strong reflection objects and calculating power in these specific orientations, the system adds spatial dimensionality to the detection process, enabling it to distinguish targets from strong reflection objects based on their directional characteristics.
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 solution enables precise detection of targets even in environments with strong reflection objects, improving the accuracy of target identification in vehicle following systems by calculating power in estimated orientations and using high-resolution arrival direction estimation methods.
Implementation Method 1
a radar apparatus that has an array antenna, estimates an arrival direction of a reflection wave by analyzing the reflection wave received by using the array antenna
Implementation Method 2
a reflection wave formed in the transmission signal is reflected on a target
Implementation Method 3
a frequency spectrum of a beat signal generated by mixing a transmission signal which is frequency-modulated and emitted and a reception signal
Implementation Method 4
generated by mixing a transmission signal which is frequency-modulated and emitted and a reception signal
Data Source
AI summary
A radar apparatus includes a retrieval unit, an estimation unit, a calculation unit, and a determination unit. The retrieval unit retrieves a strong reflection object based on a signal strength which a frequency spectrum of a beat signal generated by mixing a transmission signal which is frequency-modulated and emitted and a reception signal which is formed in the transmission signal is reflected on a target indicates. The estimation unit estimates an estimation orientation which is an orientation of a target assumed to be present around the strong reflection object, based on a relative distance to the strong reflection object. The calculation unit calculates power which is the signal strength for the estimation orientation by generating an orientation spectrum in the estimation orientation based on a frequency component corresponding to the relative distance. The determination unit determines whether there is the target in the estimation orientation based on the power.