Near object detection system

• US 6,670,910 B2
• Filed: 01/31/2002
• Issued: 12/30/2003
• Est. Priority Date: 08/16/2000
• Status: Expired due to Term

• Current Assignee: Valeo Radar Systems, Inc. (Valeo SE)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Pleva, Joseph S., Woodington, Walter Gordon, Russell, Mark E., Delcheccolo, Michael Joseph, Van Rees, H. Barteld, Firda, John M.
• Primary Examiner(s): Sotomayor, John B.
• Application Number:
  US10/062,578
• Publication Number:
  US 20020147534A1
• Time in Patent Office: 698 Days
• Field of Search: 342/70, 342/71, 342/72, 342/195, 340/435, 340/436, 340/903, 701/301
• US Class Current: 342/70
• CPC Class Codes: B60K 31/0008 including means for detecting potential obstacles in vehicle path
• CPC Class Codes: B60Q 9/008 for anti-collision purposes
• CPC Class Codes: B60T 2201/08 Lane monitoring; Lane Keeping Systems
• CPC Class Codes: B60T 2201/081 using distance control
• CPC Class Codes: B60T 2201/088 using transmission control
• CPC Class Codes: B60W 2530/10 Weight
• CPC Class Codes: B60W 2554/4043 Lateral speed
• CPC Class Codes: B60W 2554/803 Relative lateral speed
• CPC Class Codes: G01S 13/04 Systems determining presence of a target based on relative movement of target G01S13/56
• CPC Class Codes: G01S 13/282 using a frequency modulated carrier wave G01S13/286 takes precedence
• CPC Class Codes: G01S 13/343 using sawtooth modulation
• CPC Class Codes: G01S 13/346 using noise modulation
• CPC Class Codes: G01S 13/48 using multiple beams at emission or reception
• CPC Class Codes: G01S 13/584 adapted for simultaneous range and velocity measurements
• CPC Class Codes: G01S 13/723 by using numerical data
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 13/87 Combinations of radar systems, e.g. primary radar and secondary radar
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/0245 Radar with phased array antenna
• CPC Class Codes: G01S 2013/9314 Parking operations
• CPC Class Codes: G01S 2013/9315 : Monitoring blind spots
• CPC Class Codes: G01S 2013/9317 : Driving backwards
• CPC Class Codes: G01S 2013/932 : using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/9321 : Velocity regulation, e.g. cruise control
• CPC Class Codes: G01S 2013/93271 : in the front of the vehicles
• CPC Class Codes: G01S 2013/93272 : in the back of the vehicles
• CPC Class Codes: G01S 2013/93274 : on the side of the vehicles
• CPC Class Codes: G01S 2013/93275 : in the bumper area
• CPC Class Codes: G01S 7/023 : Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques auxiliary means for detecting or identifying radar signals or the like G01S7/021; means for anti-jamming G01S7/36
• CPC Class Codes: G01S 7/0232 : Avoidance by frequency multiplex
• CPC Class Codes: G01S 7/032 : Constructional details for solid-state radar subsystems
• CPC Class Codes: G01S 7/038 : Feedthrough nulling circuits
• CPC Class Codes: G01S 7/06 : Cathode-ray tube displays or other two dimensional or three-dimensional displays
• CPC Class Codes: G01S 7/288 : Coherent receivers
• CPC Class Codes: G01S 7/352 : Receivers
• CPC Class Codes: G01S 7/354 : Extracting wanted echo-signals Doppler systems G01S13/50
• CPC Class Codes: G01S 7/356 : involving particularities of FFT processing
• CPC Class Codes: G01S 7/4004 : of parts of a radar system
• CPC Class Codes: G01S 7/4008 : of transmitters
• CPC Class Codes: G01S 7/4021 : of receivers
• CPC Class Codes: H01Q 1/3233 : particular used as part of a sensor or in a security system, e.g. for automotive radar, navigation systems
• CPC Class Codes: H01Q 1/3258 : using the gutter of the vehicle; Means for clamping a whip aerial on the edge of a part of the vehicle
• CPC Class Codes: H01Q 1/3283 : side-mounted antennas, e.g. bumper-mounted, door-mounted mounted on windscreens H01Q1/1271
• CPC Class Codes: H01Q 1/38 : formed by a conductive layer on an insulating support patch antennas H01Q9/0407; microstrip dipole antennas H01Q9/065; microstrip slot antennas H01Q13/106; transmission line microstrip antennas H01Q13/206; manufacturing reflecting surfaces using insulating material for supporting the reflecting surface H01Q15/142
• CPC Class Codes: H01Q 1/42 : Housings not intimately mechanically associated with radiating elements, e.g. radome
• CPC Class Codes: H01Q 13/10 : Resonant slot antennas
• CPC Class Codes: H01Q 13/18 : the slot being backed by, or formed in boundary wall of, a resonant cavity longitudinally slotted cylinder H01Q13/12 ; Open cavity antennas
• CPC Class Codes: H01Q 21/0043 : Slotted waveguides combination with horns H01Q13/0233
• CPC Class Codes: H01Q 21/0075 : Stripline fed arrays H01Q21/065 takes precedence
• CPC Class Codes: H01Q 21/0087 : Apparatus or processes specially adapted for manufacturing antenna arrays manufacturing waveguides H01P11/00
• CPC Class Codes: H01Q 21/065 : Patch antenna array
• CPC Class Codes: H01Q 25/00 : Antennas or antenna systems providing at least two radiating patterns arrangements for changing or varying the orientation or the shape of the directional pattern H01Q3/00
• CPC Class Codes: H01Q 3/24 : varying the orientation by switching energy from one active radiating element to another, e.g. for beam switching
• CPC Class Codes: H01Q 3/40 : with phasing matrix

Abstract

A near object detection (NOD) system includes a plurality of sensors, each of the sensors for providing detection coverage in a predetermined coverage zone. Each of the sensors includes a transmit antenna for transmitting a first RF signal, a receive antenna for receiving a second RF signal and a means for sharing the target data between each of the plurality of sensors in the NOD system.

Claims

1. A near object detection system comprising:

a plurality of target sensors coupled to a vehicle, each of the target sensors for providing range cell data having local coordinates associated with each respective target sensor; and

a processor coupled to receive the range cell data having local coordinates and to process the range cell data in a vehicle global coordinate system.

2. The system of claim 1, wherein the processor comprises:

a combiner for combining track files generated by respective ones of the plurality of target sensors.

3. The system of claim 1, wherein the processor comprises:

a multi-hypothesis tracker (MHT) adapted to receive the range cell data provided by the one or more target sensors;

an association hypothesis generator coupled to the MHT;

a state variable filter coupled to the association hypothesis generator and further coupled to the MHT;

a public track generator coupled to the association hypothesis generator, wherein the public track generator transforms the local coordinates of positional tracks associated with targets to a vehicle global coordinate system;

a data fuser coupled to the public track generator, wherein the data fuser combines the data tracks associated with each of the plurality of target sensors to provide fused public tracks;

a track quality generator coupled to the data fuser, wherein the track quality generator determines data quality values associated with the fused public tracks;

a discriminator coupled to the public track generator and to the track quality generator, wherein the discriminator provides sensor scheduling information; and

a vehicle crash management operator coupled to the track quality generator and to the discriminator, wherein the vehicle crash management operator provides control actions to vehicle systems.

4. The system of claim 3, wherein the state variable filter includes a Kalman filter.

5. The system of claim 3, further comprising:

a sensor scheduler coupled to the discriminator and to at least one of the plurality of target sensors, wherein the sensor scheduler provides an update schedule associated with range cell data updates provided by the plurality of target sensors.

6. The system of claim 5, wherein the sensor scheduler further provides a beam dwell associated with at least a respective one of the plurality of sensors.

7. A near object detection system comprising:

a plurality of target sensors coupled to a vehicle, each of the target sensors for providing target data, wherein the target sensors include at least one of;

an infrared (IR) sensor and a radar sensor;

a processor for receiving the target data, processing the data and providing a processor output coupled to one or more vehicle safety systems;

wherein the processor includes a combiner for combining track files generated by respective ones of the plurality of target sensors.

8. A near object detection system comprising:

a plurality of target sensors coupled to a vehicle, each of the target sensors for providing target data, wherein the target sensors include at least one of;

an infrared (IR) sensor and a radar sensor; and

a processor for receiving the target data, processing the data and providing a processor output coupled to one or more vehicle safety systems, wherein the processor includes;

a multi-hypothesis tracker (MHT) adapted to receive the target data provided by the one or more target sensors;

an association hypothesis generator coupled to the MHT;

a state variable filter coupled to the association hypothesis generator and further coupled to the MHT;

a public track generator coupled to the association hypothesis generator, wherein the public track generator transforms the local coordinates of positional tracks associated with targets to a vehicle global coordinate system;

a data fuser coupled to the public track generator, wherein the data fuser combines the data tracks associated with each of the plurality of target sensors to provide fused public tracks;

a track quality generator coupled to the data fuser, wherein the track quality generator determines data quality values associated with the fused public tracks;

a discriminator coupled to the public track generator and to the track quality generator, wherein the discriminator provides sensor scheduling information; and

a vehicle crash management operator coupled to the track quality generator and to the discriminator, wherein the vehicle crash management operator provides control actions to the vehicle safety systems.

9. The system of claim 8, wherein the state variable filter includes a Kalman filter.

10. The system of claim 8, further comprising:

a sensor scheduler coupled to the discriminator and to at least one of the plurality of target sensors, wherein the sensor scheduler provides an update schedule associated with target data updates provided by the plurality of target sensors.

11. The system of claim 10, wherein the sensor scheduler further provides a beam dwell associated with the radar sensor.

12. A near object detection method comprising:

target tracking with a plurality of target sensors coupled to a vehicle, which provide range cell data having local coordinates associated with each respective target sensor; and

sharing the target data provided by each of the plurality of target sensors in a processor coupled to receive and process the range cell data in a vehicle global coordinate system.

13. The method of claim 12, wherein the sharing the target data comprises:

combining track files generated by respective ones of the plurality of target sensors.

14. The method of claim 12, wherein the sharing the target data comprises:

comparing track hypotheses with a multi-hypothesis tracker (MHT) adapted to receive the range cell data provided by the one or more target sensors;

testing track hypotheses with an association hypothesis generator coupled to the MHT;

filtering with a state variable filter coupled to the association hypothesis generator and further coupled to the MHT;

generating public tracks with a public track generator coupled to the association hypothesis generator, wherein the public track generator transforms the local coordinates of positional tracks associated with targets to a vehicle global coordinate system;

data fusing with a data fuser coupled to the public track generator, wherein the data fuser combines the target data associated with each of the plurality of target sensors to provide fused public tracks;

generating track quality values with a track quality generator coupled to the data fuser, wherein the track quality generator determines data quality values associated with the fused public tracks;

discriminating with a discriminator coupled to the public track generator and to the track quality generator, wherein the discriminator provides sensor scheduling information; and

controlling actions of safety systems coupled to the vehicle with a vehicle crash management operator coupled to the track quality generator and to the discriminator, wherein the vehicle crash management operator provides control actions to vehicle systems.

15. The method of claim 14, wherein the state variable filter is a Kalman filter.

16. The method of claim 14, further comprising:

scheduling the target sensors with a sensor scheduler coupled to the discriminator and to at least one of the plurality of target sensors, wherein the sensor scheduler provides an update schedule associated with target data updates provided by the plurality of target sensors.

17. The method of claim 16, further comprising:

generating with the sensor scheduler, a beam dwell associated with the radar sensor.

18. A near object detection method comprising:

target tracking with a plurality of target sensors coupled to a vehicle, each of the target sensors for providing detection coverage in a predetermined coverage zone, and each of which provides target data, wherein the target tracking includes at least one of;

imaging with an infrared (IR) sensor; and

radar sensing with a radar sensor; and

sharing the target data provided by each of the plurality of target sensors in a processor to provide a processor output coupled to one or more vehicle safety systems, wherein the sharing the target data includes combining track files generated by respective ones of the plurality of target sensors.

19. A near object detection method comprising:

target tracking with a plurality of target sensors coupled to a vehicle, each of the target sensors for providing detection coverage in a predetermined coverage zone, and each of which provides target data, wherein the target tracking includes at least one of;

imaging with an infrared (IR) sensor; and

radar sensing with a radar sensor; and

sharing the target data provided by each of the plurality of target sensors in a processor to provide a processor output coupled to one or more vehicle safety systems, wherein the sharing the target data includes;

comparing track hypotheses with a multi-hypothesis tracker (MHT) adapted to receive the target data provided by the one or more target sensors;

testing track hypotheses with an association hypothesis generator coupled to the MHT;

filtering with a state variable filter coupled to the association hypothesis generator and further coupled to the MHT;

generating public tracks with a public track generator coupled to the association hypothesis generator, wherein the public track generator transforms the local coordinates of positional tracks associated with targets to a vehicle global coordinate system;

data fusing with a data fuser coupled to the public track generator, wherein the data fuser combines the target data associated with each of the plurality of target sensors to provide fused public tracks;

generating track quality values with a track quality generator coupled to the data fuser, wherein the track quality generator determines data quality values associated with the fused public tracks;

discriminating with a discriminator coupled to the public track generator and to the track quality generator, wherein the discriminator provides sensor scheduling information; and

controlling actions of safety systems coupled to the vehicle with a vehicle crash management operator coupled to the track quality generator and to the discriminator, wherein the vehicle crash management operator provides control actions to the vehicle safety systems.

20. The method of claim 19, wherein the state variable filter is a Kalman filter.

21. The method of claim 19, further comprising:

scheduling the target sensors with a sensor scheduler coupled to the discriminator and to at least one of the plurality of target sensors, wherein the sensor scheduler provides an update schedule associated with target data updates provided by the plurality of target sensors.

22. The method of claim 21, further comprising:

generating with the sensor scheduler, a beam dwell associated with the radar sensor.