Radar Network Waveform Optimization for Velocity Range Disambiguation
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Solution Overview
Problem
Conventional radar sensor systems in autonomous vehicles face challenges in achieving high range and angular resolution simultaneously with high unambiguous velocity due to hardware limitations, particularly with increasing bandwidth leading to decreased unambiguous velocity and compromised range resolution.
Innovation Solution
A radar network with centralized processing and multiple radars employing joint waveform optimization, using different waveform parameters such as PRI and number of samples, allows for simultaneous and orthogonal transmissions to estimate unambiguous velocity and range through association of velocity vectors in a common field of view, applicable to MIMO radar sensors and distributed aperture radars.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the bandwidth of radar signals is increased to achieve finer range resolution, then range resolution is improved, but unambiguous velocity decreases
Solution Approach 1:
The system divides the radar network into multiple radar sensors, each transmitting signals with different bandwidths. This segmentation allows the network to simultaneously achieve fine range resolution (through wide bandwidth radars) and high unambiguous velocity (through narrow bandwidth radars with low PRI), resolving the contradiction by distributing different functional specializations across multiple sensors.
Solution Approach 2:
The patent changes the bandwidth parameter of radar signals transmitted by different radar sensors in the network. By assigning different bandwidth values to different radars, the system enables some radars to optimize for range resolution while others optimize for velocity measurement, and the central processing unit integrates these complementary measurements.
2Speed
If the pulse repetition interval (PRI) is decreased to allow for higher unambiguous velocity, then unambiguous velocity is improved, but range resolution deteriorates
Solution Approach 1:
The radar network segments the velocity measurement function across multiple sensors. Radars with low PRI are dedicated to velocity measurement, while radars with wide bandwidth are dedicated to range resolution. The central processing unit combines these segmented measurements to achieve both high velocity accuracy and fine range resolution simultaneously.
Solution Approach 2:
The patent transitions from a single-radar system to a multi-radar network dimension. This dimensional change allows the system to add another degree of freedom by varying bandwidth across different radars in the network, enabling simultaneous optimization of both velocity and range resolution through coordinated multi-radar operation.
3Measurement precision
If ADC sampling rates are increased to support wider bandwidth radar signals, then range resolution is improved, but hardware complexity and cost increase
Solution Approach 1:
The system segments the high-bandwidth measurement function across multiple radars rather than requiring a single radar with extremely high ADC sampling rates. Each radar uses moderate bandwidth and corresponding ADC rates, but the network collectively achieves the equivalent of a wideband system, reducing individual hardware complexity while maintaining overall measurement precision.
Solution Approach 2:
The central processing unit acts as an intermediary that receives and integrates data from multiple radars with different bandwidth configurations. This intermediary processing enables the network to achieve fine range resolution through combined data from multiple moderate-bandwidth radars, avoiding the need for any single radar to have extremely high ADC sampling rates.
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
Enables accurate estimation of unambiguous velocity and range by disambiguating ambiguous values across multiple radars, maintaining high resolution capabilities while overcoming hardware limitations, applicable to autonomous vehicles, aircrafts, and watercrafts.
Implementation Method 1
Radar sensor systems emit radar signals into a surrounding environment. The radar sensor signals reflect off objects in the environment and the radar sensor system then detects the reflected radar signals.
Implementation Method 2
Radar sensor systems are able to capture velocity information nearly instantaneously... dimensions include range, doppler, and beam
Data Source
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AI summary
A radar sensor system comprises a first radar sensor and at least a second radar sensor and one or more processors configured to assign different pulse rate intervals (PRI) to the first radar sensor and the second radar sensor. The processor(s)s are further configured to: receive ambiguous velocity estimates from the first and second radar sensors, respectively; determine maximum detectable velocity (Vmax) values for the first and second radar sensors based on their respective PRIs; generate a first velocity vector for the first radar sensor based on the first Vmax and the first ambiguous velocity estimate; generate a second velocity vector for the second radar sensor based on the second Vmax and the second ambiguous velocity estimate; compare velocity values in the first and second velocity vectors; and identify and output a velocity value common to the first and second velocity vectors as a correct unambiguous velocity of the object.