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US6085151A Expired / Lapsed US ⏱️ 0.0 years remaining

Predictive collision sensing system

Assignee: Joyson Safety Systems Acquisition LLC
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Filing: 1998-01-20
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Granted: 2000-07-04
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Expires: 2018-01-20
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Abstract

Abstract A relatively narrow beam of either RF or optical electromagnetic radiation is scanned over a relatively wide azimuthal range. The return signal is processed to detect the range and velocity of each point of reflection. Individual targets are identified by clustering analysis and are tracked in a Cartesian coordinate system using a Kalman filter. The threat to the vehicle for a given target is assessed from estimates of the relative distance, velocity, and size of each target, and one or more vehicular devices are controlled responsive to the assessment of threat so as to enhance the safety of the vehicle occupant. In a preferred embodiment, a quantized linear frequency modulated continuous wave RF signal is transmitted from and received by a multi-beam antenna having an aziumthal range of at least +/-100 degrees and an individual beam width of approximately 10 degrees.

Inventors

  • 👤 Michael E. Farmer
  • 👤 Michael P. Bruce

Bibliographic Details

Application Number —
Jurisdiction US
Data Source google_patents
Last Synchronized 2026-10-25 20:04
CPC Classifications
G; G01; G01S; G01S7/00; G01S7/02; G01S7/023; G01S13/00; G01S13/02; G01S13/06; G01S13/42; G01S13/88; G01S13/93; G01S13/931; G01S17/00; G01S17/88; G01S17/93; G01S17/931; G01S7/0232; G01S7/0234; G01S7/03; B; B60; B60R; B60R21/00; B60R21/01; B60R21/013; B60R21/0134; B60T; B60T2201/00; B60T2201/02; B60T2201/022; G01S13/08; G01S13/32; G01S13/34; G01S13/66; G01S13/72; G01S13/723; G01S13/726; G01S2013/0236; G01S2013/0245; G01S2013/9318; G01S2013/93185; G01S2013/9327; G01S2013/93271; G01S2013/93273; G01S2013/93275; G01S2013/93276; G01S7/48; G01S7/491; G01S7/493

Claims Analysis

Total Claims: 33
Claim 1
Independent Claim 227 words
A predictive collision sensing system for a vehicle, comprising: a. a radar transmitter/receiver module for illuminating a zone proximate the vehicle with a beam of electromagnetic energy and for receiving portions of said beam of electromagnetic energy reflected by one or more objects illuminated by said electromagnetic energy thereby providing an estimate of the distance to said target relative to the vehicle; b. a signal processor operatively coupled to said radar transmitter/receiver module; c. a means under control of said signal processor for scanning said beam of electromagnetic energy over an azimuth range in accordance with an azimuth coverage pattern, wherein said azimuth coverage pattern is continuous; d. a target tracking algorithm implemented by said signal processor for tracking said one or more objects relative to the vehicle; e. a clustering algorithm implemented by said signal processor for grouping separate tracks of said one or more objects; f. a target size estimating algorithm implemented by said signal processor for estimating the azimuthal extent of said one or more objects tracked by said target tracking algorithm; and g. a threat assessment algorithm implemented by said signal processor for assessing the threat of said one or more objects to the vehicle, whereby said signal processor controls one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.
Claim 2
Dependent Claim 227 words
A predictive collision sensing system for a vehicle, comprising: a. a radar transmitter/receiver module for illuminating a zone proximate the vehicle with a beam of electromagnetic energy and for receiving portions of said beam of electromagnetic energy reflected by one or more objects illuminated by said electromagnetic energy thereby providing an estimate of the distance to said target relative to the vehicle; b. a signal processor operatively coupled to said radar transmitter/receiver module; c. a means under control of said signal processor for scanning said beam of electromagnetic energy over an azimuth range in accordance with an azimuth coverage pattern, wherein said azimuth coverage pattern is continuous; d. a target tracking algorithm implemented by said signal processor for tracking said one or more objects relative to the vehicle; e. a clustering algorithm implemented by said signal processor for grouping separate tracks of said one or more objects; f. a target size estimating algorithm implemented by said signal processor for estimating the azimuthal extent of said one or more objects tracked by said target tracking algorithm; and g. a threat assessment algorithm implemented by said signal processor for assessing the threat of said one or more objects to the vehicle, whereby said signal processor controls one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.
Claim 3
Dependent Claim 37 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said radar transmitter/receiver module further provides an estimate of the velocity relative to the vehicle for each of said one or more objects.
Claim 4
Dependent Claim 28 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said radar transmitter/receiver module incorporates an antenna having a plurality of distinct beam positions.
Claim 5
Dependent Claim 22 words
A predictive collision sensing system for a vehicle as recited in claim 3, wherein said radar transmitter/receiver module incorporates a multi-beam antenna.
Claim 6
Dependent Claim 37 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein the range of azimuth angles associated with said azimuth coverage pattern is at least +/-100 degrees relative to the front of the vehicle.
Claim 7
Dependent Claim 26 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein the size of said beam of electromagnetic energy is approximately 10 degrees.
Claim 8
Dependent Claim 67 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said beam of electromagnetic energy is sequentially scanned over said azimuth coverage pattern if said target tracking algorithm is not tracking an object, and said beam of electromagnetic energy is adaptively scanned responsive to the path of said one or more objects when target tracking algorithm is tracking said one or more objects.
Claim 9
Dependent Claim 31 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein the trajectory of said one or more objects is tracked in Cartesian coordinates relative to the vehicle.
Claim 10
Dependent Claim 22 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said target tracking algorithm incorporates a Kalman filter.
Claim 11
Dependent Claim 27 words
A predictive collision sensing system for a vehicle as recited in claim 9, wherein said Kalman filter is augmented with a state to track the target size.
Claim 12
Dependent Claim 47 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said one or more vehicular devices are selected from the group consisting of one or more warning devices, the vehicle braking system, the vehicle steering system, and one or more occupant restraint devices.
Claim 13
Dependent Claim 23 words
A predictive collision sensing system for a vehicle as recited in claim 11, wherein said radar transmitter/receiver module operates in the pulsed mode.
Claim 14
Dependent Claim 25 words
A predictive collision sensing system for a vehicle as recited in claim 12, wherein said linear frequency modulated continuous wave mode incorporates a quantized waveform.
Claim 15
Dependent Claim 27 words
A predictive collision sensing system for a vehicle as recited in claim 11, wherein said radar transmitter/receiver module operates in the linear frequency modulated continuous wave mode.
Claim 16
Dependent Claim 32 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said electromagnetic energy comprises energy selected from group consisting of RF energy, microwave energy, and millimeter wave energy.
Claim 17
Dependent Claim 20 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said electromagnetic energy comprises optical energy.
Claim 18
Dependent Claim 31 words
A predictive collision sensing system for a vehicle as recited in claim 1, wherein said clustering algorithm is responsive to range, cross-range, and speed in accordance with a normalized distance function.
Claim 19
Independent Claim 143 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto, comprising: a. measuring the range of one or more objects relative to the vehicle using an azimuthally scanned radar beam; b. calculating the trajectory of said one or more objects from said range measurements; c. clustering separate tracks of said one or more objects; d. measuring the azimuthal extent of said one or more objects from said range measurements and from the azimuthal scan angle of said radar beam; e. assessing the threat of said one or more objects to the vehicle from a combination of said trajectory and said azimuthal extent of said one or more objects; and f. controlling one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.
Claim 20
Independent Claim 143 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto, comprising: a. measuring the range of one or more objects relative to the vehicle using an azimuthally scanned radar beam; b. calculating the trajectory of said one or more objects from said range measurements; c. clustering separate tracks of said one or more objects; d. measuring the azimuthal extent of said one or more objects from said range measurements and from the azimuthal scan angle of said radar beam; e. assessing the threat of said one or more objects to the vehicle from a combination of said trajectory and said azimuthal extent of said one or more objects; and f. controlling one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.
Claim 21
Dependent Claim 47 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, further comprising the operation of radar sensing the velocity of one or more objects relative to the vehicle using a scanned radar beam.
Claim 22
Dependent Claim 47 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein the scanning of said scanned radar beam is responsive to said threat assessment of said one or more objects to the vehicle.
Claim 23
Dependent Claim 41 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein said trajectory of said one or more objects is calculated in Cartesian coordinates by Kalman filtering.
Claim 24
Dependent Claim 39 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein said aziumuthal extent of said one or more objects is estimated by clustering analysis.
Claim 25
Dependent Claim 34 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein said threat assessment incorporates an estimate of crash severity.
Claim 26
Dependent Claim 33 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, said threat assessment incorporates an estimate of crash time.
Claim 27
Dependent Claim 33 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, said threat assessment incorporates an estimate of crash direction.
Claim 28
Dependent Claim 33 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, said threat assessment incorporates an estimate of crash probability.
Claim 29
Dependent Claim 58 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein said one or more vehicular devices are selected from the group consisting of one or more warning devices, the vehicle braking system, the vehicle steering system, and one or more occupant restraint devices.
Claim 30
Dependent Claim 60 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein the clustering of said separate tracks of said one or more objects comprises the step of calculating a normalized distance function that is responsive to range, range variance, cross-range, cross-range variance, speed, and speed variance.
Claim 31
Dependent Claim 37 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto as recited in claim 18, wherein said Kalman filter is augmented with a state to track target size.
Claim 32
Independent Claim 387 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto, comprising: a. measuring the range of one or more objects relative to the vehicle using an azimuthally scanned radar beam; b. measuring the velocity of one or more objects relative to the vehicle using said azimuthally scanned radar beam, wherein the operations of measuring the range and velocity of one or more objects relative to the vehicle using said azimuthally scanned radar beam comprises: i. generating a continuous wave RF signal comprising a repetitive sequence of uniformly spaced frequencies so as to form a transmitted signal; ii. illuminating the object with said continuous wave RF signal; iii. receiving the component of said RF signal reflected by said one or more objects so as to form a received signal; iv. mixing said received signal with said transmitted signal so as to form a complex amplitude frequency difference signal from the difference in frequency therebetween; v. comparing the real part of said complex frequency difference signal with a plurality of monotonically increasing threshold values, wherein adjacent threshold values corresponds to the bounds of an associated range cell, vi. storing the complex amplitudes of said received signal for each said associated range cell so as to form an associated list of complex amplitudes; vii. calculating the Doppler shift for each said associated range cell from a spectral analysis of said associated list of complex amplitudes; and viii. collecting said Doppler shift calculations for all said associated range cells so as to form a range-Doppler map for said one or more objects, thereby providing the distance and velocity of said one or more objects relative to the vehicle; c. calculating the trajectory of said one or more objects from said range measurements; d. clustering separate tracks of said one or more objects; e. measuring the azimuthal extent of said one or more objects from said range measurements and from the azimuthal scan angle of said radar beam; f. assessing the threat of said one or more objects to the vehicle from a combination of said trajectory and said azimuthal extent of said one or more objects; and g. controlling one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.
Claim 33
Independent Claim 387 words
A method of predicting a crash for a vehicle and for controlling one or more vehicular devices responsive thereto, comprising: a. measuring the range of one or more objects relative to the vehicle using an azimuthally scanned radar beam; b. measuring the velocity of one or more objects relative to the vehicle using said azimuthally scanned radar beam, wherein the operations of measuring the range and velocity of one or more objects relative to the vehicle using said azimuthally scanned radar beam comprises: i. generating a continuous wave RF signal comprising a repetitive sequence of uniformly spaced frequencies so as to form a transmitted signal; ii. illuminating the object with said continuous wave RF signal; iii. receiving the component of said RF signal reflected by said one or more objects so as to form a received signal; iv. mixing said received signal with said transmitted signal so as to form a complex amplitude frequency difference signal from the difference in frequency therebetween; v. comparing the real part of said complex frequency difference signal with a plurality of monotonically increasing threshold values, wherein adjacent threshold values corresponds to the bounds of an associated range cell, vi. storing the complex amplitudes of said received signal for each said associated range cell so as to form an associated list of complex amplitudes; vii. calculating the Doppler shift for each said associated range cell from a spectral analysis of said associated list of complex amplitudes; and viii. collecting said Doppler shift calculations for all said associated range cells so as to form a range-Doppler map for said one or more objects, thereby providing the distance and velocity of said one or more objects relative to the vehicle; c. calculating the trajectory of said one or more objects from said range measurements; d. clustering separate tracks of said one or more objects; e. measuring the azimuthal extent of said one or more objects from said range measurements and from the azimuthal scan angle of said radar beam; f. assessing the threat of said one or more objects to the vehicle from a combination of said trajectory and said azimuthal extent of said one or more objects; and g. controlling one or more vehicular devices responsive to said assessment of threat, so as to enhance the safety of the occupant of the vehicle.

USPTO Annuity & Maintenance Windows

Annuity Stage Window Opens Payment Deadline Surcharge Period Until Estimated Fee Status
3.5 Years (Year 4) 2003-07-04 2004-01-03 2004-07-04 $2000.00 Window Closed / Lapsed
7.5 Years (Year 8) 2007-07-04 2008-01-03 2008-07-04 $3760.00 Window Closed / Lapsed
11.5 Years (Year 12) 2011-07-04 2012-01-03 2012-07-04 $7700.00 Window Closed / Lapsed

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