IP Library › Granted Patent US 12,736,663
Granted Patent B2
US 12,736,663 · App. 18/367,427 · Granted Sep 15, 2026

Radar system transmitter beamforming using occupancy map data

Inventors: Ashish Pandharipande (Eindhoven, NL); Nitin Jonathan Myers (Rozenburg, NL); Edoardo Focante (Delft, NL); Geethu Joseph (Delft, NL)
Assignee: NXP B.V.
G01S13/878G01S7/023G01S7/032G01S13/584
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Quick Facts
Patent No.
US 12,736,663
App. No.
18/367,427
Granted
Sep 15, 2026
Kind
B2
Abstract

A device may include at least one transmitter unit and at least one receiver unit, wherein the at least one transmitter unit and the at least one receiver unit are configured to transmit and receive radar signals, wherein the at least one transmitter unit and the at least one receiver unit are co-located with a vehicle. A device may include a radar processor, configured to: determine an occupancy map, wherein the occupancy map identifies a location of an object with respect to the automotive radar system, determine, using the occupancy map, a beamforming weight vector w, and transmit, using the at least one transmitter unit, the radar signal using the beamforming weight vector w.

Claims (45)

1 . An automotive radar system, comprising:

at least one transmitter unit and at least one receiver unit, wherein the at least one transmitter unit and the at least one receiver unit are configured to transmit and receive radar signals, wherein the at least one transmitter unit and the at least one receiver unit are co-located with a vehicle; and

a radar processor, configured to:

determine an occupancy map, wherein the occupancy map identifies a location of an object with respect to the automotive radar system and a probability value associated with the location of the object in the occupancy map,

determine, using the occupancy map, a beamforming weight vector w, wherein the beamforming weight vector w is configured to enable determination of a gain of the radar signal and the gain of the radar signal is at least partially determined by the probability value associated with the location, by optimizing the beamforming weight vector w so that radar signals transmitted to the location have a first gain when the probability value has a first probability value and a second gain when the probability value has a second probability value, wherein the first gain is greater than the second gain when the first probability value indicates higher uncertainty than the second probability value, and

transmit, using the at least one transmitter unit, the radar signal using the beamforming weight vector w.

2 . The automotive radar system of claim 1 , wherein the beamforming weight vector w is configured to enable a determination of a beam of the radar signal has an effective range that is less than or equal to a distance between the automotive radar system and the object.

3 . The automotive radar system of claim 1 , wherein the radar processor is configured to determine the occupancy map by:

determining a location of the automotive radar system; and

accessing a database storing locations of a plurality of objects to identify the object, wherein the location of the object is within a threshold distance of the location of the automotive radar system.

4 . The automotive radar system of claim 1 , wherein the radar processor is configured to determine the occupancy map by:

receiving, using the at least one receiver unit, a received radar signal;

processing the received radar signal to identify a target object and a range to the target object; and

determine the occupancy map using the range to the target object.

5 . The automotive radar system of claim 1 , wherein a field of vision of the automotive radar system is divided into a plurality of angle bins and the occupancy map defines distance values in association with angle bins of the plurality of angle bins.

6 . The automotive radar system of claim 5 , wherein the radar processor is configured to determine the beamforming weight vector w by determining a maximum value of the weight vector w that satisfies a requirement that an effective range of beams of the radar signal transmitted into each angle bin do not exceed the distance values associated with the same angle bin in the occupancy map.

7 . The automotive radar system of claim 1 , wherein the occupancy map associates a probability value with the location of the object.

8 . The automotive radar system of claim 1 , wherein the object includes at least one of a static object and a dynamic object, wherein the static object may be an object selected from a guardrail, a building, a street obstruction, and a vegetation, and the dynamic object may be an object selected from a pedestrian, a cyclist, an automobile, and another type of moving vehicle.

9 . A system, comprising:

at least one transmitter unit and at least one receiver unit; and

a controller, configured to:

determine an occupancy map, wherein the occupancy map identifies a location and a probability value associated with the location,

determine, using the occupancy map, a beamforming weight vector, wherein the beamforming weight vector is configured to enable a determination of a gain of a radar signal, wherein the gain is at least partially determined by the probability value associated with the location in the occupancy map, by optimizing the beamforming weight vector so that radar signals transmitted to the location have a first gain when the probability value has a first probability value and a second gain when the probability value has a second probability value, wherein the first gain is greater than the second gain when the first probability value indicates higher uncertainty than the second probability value, and

transmit, using the at least one transmitter unit, the radar signal using the beamforming weight vector.

10 . The system of claim 9 , wherein the beamforming weight vector is configured to enable a determination of an effective range of a beam of the radar signal that is less than or equal to a value determined by the location in the occupancy map.

11 . The system of claim 9 , wherein the controller is configured to determine the occupancy map by:

determining a location of a radar system; and

accessing a database storing locations of a plurality of objects to identify the object, wherein the location of the object is within a threshold distance of the location of the radar system.

12 . The system of claim 9 , wherein the controller is configured to determine the occupancy map by:

processing a received radar signal to identify a target object and a range to the target object; and

determine the occupancy map using the range of the target object.

13 . A method, comprising:

determining an occupancy map, wherein the occupancy map identifies a location of an object with respect to a radar system and a probability value associated with the object;

determining, using the occupancy map, a beamforming weight vector, wherein the beamforming weight vector is configured to enable a determination of a gain of a radar signal, wherein the gain is at least partially determined by the probability value associated with the location in the occupancy map, by optimizing the beamforming weight vector so that radar signals transmitted to the location have a first gain when the probability value has a first probability value and a second gain when the probability value has a second probability value, wherein the first gain is greater than the second gain when the first probability value indicates higher uncertainty than the second probability value; and

transmitting, using at least one transmitter unit of the radar system, a radar signal using the beamforming weight vector, wherein a gain of the radar signal is at least partially determined by the probability value.

14 . The method of claim 13 , further comprising determining the occupancy map by:

determining a location of the radar system; and

accessing a database storing locations of a plurality of objects to identify an object associated with the location.

15 . The method of claim 13 , further comprising determining the occupancy map by:

receiving a received radar signal;

processing the received radar signal to identify a target object and a range to the target object; and

determining the occupancy map using the range to the target object.

16 . The method of claim 13 , wherein a field of vision of the radar system is divided into a plurality of angle bins and the occupancy map defines distance values in association with angle bins of the plurality of angle bins.

17 . The method of claim 16 , further comprising determining the beamforming weight vector by determining a maximum value of the weight vector that satisfies a requirement that an effective range of signals transmitted into each angle bin using the weight vector do not exceed the distance value associated with the same angle bin in the occupancy map.

18 . The method of claim 13 , wherein transmitting the radar signal further comprising setting a configuration of a power amplifier in the at least one transmitter unit using the beamforming weight vector.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 25, 2025
From: MYERS, NITIN JONATHAN; FOCANTE, EDOARDO; JOSEPH, GEETHU
To: NXP B.V.
Reel/Frame 072111/0455 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 16, 2023
From: PANDHARIPANDE, ASHISH
To: NXP B.V.
Reel/Frame 064928/0629 →
Continuity (1)
Related Publication 20250085414A1 · Mar 13, 2025
References Cited (45)
US 3727218A · Cantwell, Jr. · 1973 [cited by examiner]
US 5598163A · Cornic et al. · 1997 [cited by applicant]
US 6894642B2 · Li · 2005 [cited by examiner]
US 7345620B2 · Voigtlaender · 2008 [cited by examiner]
US 7411542B2 · O'Boyle · 2008 [cited by examiner]
US 8358239B2 · Krich · 2013 [cited by examiner]
US 9229100B2 · Lee · 2016 [cited by examiner]
US 9825360B2 · Miller · 2017 [cited by examiner]
US 10942256B2 · Achour · 2021 [cited by examiner]
US 11005179B2 · Achour · 2021 [cited by examiner]
US 11119478B2 · McArthur · 2021 [cited by examiner]
US 11474229B2 · Cottron · 2022 [cited by examiner]
US 11988741B2 · Somanath · 2024 [cited by examiner]
US 12340967B2 · Sprenkle · 2025 [cited by examiner]
US 12352850B1 · Srivastav · 2025 [cited by examiner]
US 20050073457A1 · Li · 2005 [cited by examiner]
US 20060109170A1 · Voigtlaender · 2006 [cited by examiner]
US 20060267830A1 · O'Boyle · 2006 [cited by examiner]
US 20110241931A1 · Krich · 2011 [cited by examiner]
US 20150084810A1 · Lee · 2015 [cited by examiner]
US 20150355313A1 · Li et al. · 2015 [cited by applicant]
US 20160211577A1 · Miller · 2016 [cited by examiner]
US 20180348343A1 · Achour · 2018 [cited by examiner]
US 20180351250A1 · Achour · 2018 [cited by examiner]
US 20190339376A1 · Levy-Israel · 2019 [cited by examiner]
US 20200019160A1 · McArthur · 2020 [cited by examiner]
US 20200150259A1 · Cottron · 2020 [cited by examiner]
US 20210257732A1 · Achour · 2021 [cited by examiner]
US 20220196830A1 · Somanath · 2022 [cited by examiner]
US 20230013095A1 · Sprenkle · 2023 [cited by examiner]
US 20230124953A1 · Kanemoto · 2023 [cited by examiner]
US 20230269676A1 · Mandelli · 2023 [cited by examiner]
US 20250076445A1 · Ashour · 2025 [cited by examiner]
Lee, G., “Robust measurement validation for radar target tracking using prior information”, IET Radar, Sonar and Navigation, Jul. 2019. [cited by applicant]
Li, F., “A waveform design method for suppressing range sidelobes in desired intervals”, Elsevier, Signal Processing, Oct. 12, 2013. [cited by applicant]
Porebski, J., “Occupancy Grid for Static Environment Perception in Series Automotive Applications”, IFAC Papers Online, vol. 52, Issue 8, pp. 148-153, Jul. 2019. [cited by applicant]
Saval-Calvo, M., “A Review of the Bayesian Occupancy Filter”, MDPI Sensors, Feb. 2017. [cited by applicant]
Xu, C., “MIMO Radar Transmit Signal Optimization for Target Localization Exploiting Prior Information”, Computer Science, Information Theory, May 15, 2023. [cited by applicant]
Xu, F., “Transmit Beamspace DDMA Based Automotive MIMO Radar”, IEEE Transactions on Vehicular Technology, vol. 71, No. 2, Feb. 2022. [cited by applicant]
Xu, Feng et al., “Transmit Beamspace DDMA Based Automotive MIMO Radar,” IEEE Transactions on Vehicular Technology, Feb. 2022, vol. 71, No. 2, pp. 1669-1684, IEEE Transactions on Vehicular Technology. [cited by applicant]
Porebski, Jakub et al., “Occupancy grid for static environment perception in series automotive application”, Science Direct, 2019, pp. 148-153, vol. 52, IFAC (International Federation of Automatic Control), papers onlin… [cited by applicant]
Saval-Calvo, Marcelo et al, “A Review of the Bayesian Occupancy Filter”, Sensors. Feb. 10, 2017, pp. 1-18, 17, 344, MDPI, Basel, Switzerland. [cited by applicant]
Lee, G., Kwon et al., “Robust measurement validation for radar target tracking using prior information” IET Radar Sonar Navigation, 2019, pp. 1842-1849, vol. 13, Iss. 10, the Institution of Engineering and Technology. [cited by applicant]
Xu, Chan et al., “MIMO Radar Transmit Signal Optimization for Target Localization Exploiting Prior Information.” 2023, 6 pages, Department of Electronic and Information Engineering, Hong Kong. [cited by applicant]
Li, Feng-Cong et al., “A waveform design method for suppressing range sidelobes in desired intervals”, Signal Processing , vol. 96, Part B, 2014, pp. 203-211, Harbin Institute of Technology, China. [cited by applicant]