Method and Apparatus For Self Calibration of A Vehicle Radar System

• US 20150070207A1
• Filed: 09/06/2013
• Published: 03/12/2015
• Est. Priority Date: 09/06/2013
• Status: Abandoned Application

• Current Assignee: Valeo Radar Systems, Inc. (Valeo SE)
• Original Assignee: Valeo Radar Systems, Inc. (Valeo SE)
• Inventors: Millar, Jeffrey, Sturm, Christian, Insana, David, Krupinski, Kevin
• Application Number:
  US14/020,053
• Publication Number:
  US 20150070207A1
• Time in Patent Office: Days
• US Class Current: 342/174
• CPC Class Codes: G01S 13/006 Theoretical aspects G01S7/418, G01S13/9094, G01S13/958 take precedence
• CPC Class Codes: G01S 13/343 using sawtooth modulation
• CPC Class Codes: G01S 13/4454 phase comparisons monopulse, i.e. comparing the echo signals received by an interferometric antenna arrangement
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/9315 Monitoring blind spots
• CPC Class Codes: G01S 2013/93274 on the side of the vehicles
• CPC Class Codes: G01S 7/35 Details of non-pulse systems
• CPC Class Codes: G01S 7/4026 Antenna boresight
• CPC Class Codes: G01S 7/403 in azimuth, i.e. in the horizontal plane
• CPC Class Codes: G01S 7/4091 during normal radar operation

Abstract

A radar sensor for use within a vehicle includes self calibration functionality for performing angle calibrations for the sensor when the sensor is mounted within the vehicle. In at least one embodiment, the radar sensor collects information on stationary infrastructure around the vehicle for use in calibration operations. The infrastructure information may be used to generate a Doppler Monopulse Image (DMI) or other graph for the sensor. A clutter ridge within the DMI or other graph may then be analyzed to determine calibration data for the sensor.

Claims

1. A machine implemented method for use in self calibration of a radar sensor mounted to a vehicle, the method comprising:

collecting information on stationary structures in a vicinity of the vehicle using the radar sensor as the vehicle travels past the stationary structures;

generating a graph that plots normalized Doppler against monopulse phase difference or monopulse angle based on range/Doppler bins in the collected information, wherein normalized Doppler includes a ratio of radial velocity Vr to host velocity Vh, the graph having a clutter ridge comprising points representative of the stationary structures; and

analyzing the clutter ridge of the graph to identify signal strength peaks associated with different normalized Doppler values and using the peaks to generate calibration values for the radar sensor.

2. The method of claim 1, further comprising:

comparing the clutter ridge of the graph to an original phase curve associated with the radar sensor to determine a mounting angle of the sensor on the vehicle, the original phase curve including angle calibration information in sensor coordinates.

3. The method of claim 2, wherein comparing the clutter ridge to the original phase curve includes:

calculating a correlation value for the clutter ridge and the original phase curve for each of a plurality of different test mounting angles; and

determining a mounting angle of the sensor based on the correlation values.

4. The method of claim 1, wherein:

collecting information includes transmitting RF signals toward stationary structures, receiving return signals at a first and second receive antenna, and processing the return signals using a 2-dimensional DFT to form an array of range-Doppler bins for each receive antenna; and

generating a graph includes plotting information to the graph for each of the range-Doppler bins in the array of range-Doppler bins, regardless of signal strength.

5. The method of claim 4, wherein:

generating a graph includes generating a Doppler Monopulse Image (DMI).

6. The method of claim 1, further comprising:

analyzing the clutter ridge of the graph to determine variance values associated with identified peak values.

7. The method of claim 6, further comprising:

determining whether to update a tracking filter based, at least in part, on measured variance values.

8. The method of claim 1, wherein:

calibration values of the radar sensor are stored within non-volatile storage within the sensor,

the method further comprising;

analyzing the collected information to determine quality metrics for the information; and

determining whether to update stored calibration data based, at least in part, on the quality metrics.

9. The method of claim 1, wherein:

analyzing the clutter ridge of the graph to identify signal strength peaks associated with different normalized Doppler values and using the peaks to generate calibration values for the radar sensor includes;

for a first normalized Doppler value associated with a first angle of arrival, scanning to find a first peak value in the clutter ridge; and

for the first peak value, scanning to find a monopulse phase difference that corresponds to the first angle of arrival.

10. A radar sensor for use in a vehicle, the radar sensor comprising:

an RF transmitter to generate radio frequency (RF) transmit signals;

a transmit antenna to transmit the RF transmit signals;

first and second receive antennas to receive return signals representing reflections of the RF transmit signals from objects and structures within a region of interest about the vehicle;

first and second analog-to-digital converters to digitize signals associated with the first and second receive antennas, respectively; and

one or more digital processors to perform self-calibration for the radar sensor to calibrate the sensor for angle-of-arrival when it is mounted in a vehicle, wherein the one or more digital processors are configured to;

collect information on stationary infrastructure about the vehicle while the vehicle is in motion for use in self-calibration;

generate a graph that plots normalized Doppler against monopulse phase difference or monopulse angle based on range/Doppler bins in the collected information, wherein normalized Doppler includes a ratio of radial velocity Vr to host velocity Vh, the graph having a clutter ridge comprising points representative of the stationary infrastructure;

analyze the clutter ridge of the graph to identify signal strength peak values associated with different monopulse phase differences; and

generate calibration values for the radar sensor based on the peak values.

11. The radar sensor of claim 10, wherein:

the one or more digital processors are configured to analyze the clutter ridge of the graph to estimate a mounting angle of the sensor on the vehicle.

12. The radar sensor of claim 11, wherein:

the one or more digital processors are configured to analyze a zero Doppler line of the graph to estimate the mounting angle of the sensor on the vehicle.

13. The radar sensor of claim 11, wherein:

the one or more digital processors are configured to analyze the clutter ridge of the DMI to estimate the mounting angle of the sensor by performing a correlation operation between the clutter ridge and an original phase curve of the sensor at a number of different test mounting angles, the original phase curve including angle calibration information for the sensor in sensor coordinates.

14. The radar sensor of claim 10, wherein:

the one or more digital processors are configured to generate the graph using the collected information by plotting normalized Doppler versus monopulse phase difference or monopulse angle for a multitude of range/Doppler bins associated with the collected information, wherein normalized Doppler includes a ratio of radial velocity Vr to host velocity Vh.

15. The radar sensor of claim 10, wherein:

the one or more digital processors are configured to analyze the clutter ridge of the graph to determine variance values associated with the identified peak values.

16. The radar sensor of claim 15, wherein:

the one or more digital processors are configured to determine whether to update a tracking filter based, at least in part, on measured variance values.

17. The radar sensor of claim 10, further comprising:

digital storage to store calibration values for the sensor,

wherein the one or more digital processors are configured to;

analyze the collected information to determine quality metrics for the information; and

determine whether to update calibration data stored in the digital storage using new calibration values based, at least in part, on the quality metrics.

18. The radar sensor of claim 17, wherein:

the one or more digital processors are configured to update a stored calibration value when a newly generated calibration value has a higher quality metric value than the stored calibration value.

19. The radar sensor of claim 10, wherein:

the one or more digital processors are configured to generate the graph as a Doppler-Monopulse image (DMI).