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Vehicle self-carried positioning method and system thereof

  • US 6,477,465 B1
  • Filed: 10/31/2000
  • Issued: 11/05/2002
  • Est. Priority Date: 11/29/1999
  • Status: Expired due to Term
First Claim
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1. A vehicle self-carried positioning system, comprising:

  • an inertial measurement unit, carried in a vehicle, for sensing traveling displacement motions of said vehicle so as to produce digital angular increments and velocity increments signals in response to said traveling displacement motions of said vehicle;

    a north finder, carried in said vehicle, to produce a heading measurement of said vehicle;

    a velocity producer, carried in said vehicle, for producing a current axis velocity data of a body frame of said vehicle; and

    a navigation processor, which is connected with said inertial measurement unit, said north finder, and said velocity producer so as to receive said digital angular increments and velocity increments signals, heading measurement, and current axis velocity data of said body frame, for comparing an IMU position deduced from said digital angular increments and velocity increments signals with a measured position deduced from said heading measurement and current axis velocity data of said body frame, so as to obtain a position difference; and

    feeding back said position difference to correct said IMU position to output a corrected IMU position when said position difference is bigger than a predetermined scale value;

    wherein said navigation processor further comprises;

    an INS computation module, using said digital angular increments and velocity increments signals from said inertial measurement unit to produce inertial positioning measurements;

    a magnetic sensor processing module for producing a heading angle;

    a vehicle producer processing module for producing relative position error measurements for a Kalman filter; and

    an integration Kalman filter for estimating errors of said inertial positioning measurements to calibrate inertial positioning measurement errors;

    wherein said INS computation module further comprises;

    a sensor compensation module for calibrating errors of said digital angular increments and velocity increments signals; and

    an inertial navigation algorithm module for computing IMU position, velocity and attitude data;

    wherein said inertial navigation algorithm module further comprises;

    an attitude integration module for integrating said angular increments into said attitude data;

    a velocity integration module for transforming said measured velocity increments into a suitable navigation coordinate frame by using said attitude data, wherein said transformed velocity increments is integrated into said velocity data; and

    a position module for integrating said navigation frame velocity data into said position data;

    wherein said velocity producer processing module further comprises;

    a transformation module for transforming an input velocity data expressed in said body frame to a velocity expressed in a navigation frame;

    a scale factor and misalignment error compensation module for compensating scale factor and misalignment errors in said velocity; and

    a relative position computation for receiving said IMU velocity and attitude data and compensated velocity to form said relative position error measurements for said Kalman filter;

    wherein said Kalman filter module further comprises;

    a motion test module for determining whether said vehicle stops automatically;

    a measurement and time varying matrix formation module for formulating measurement and time varying matrix for a state estimation module according to motion status of said vehicle from said motion test module; and

    a state estimation module for filtering said measurement and obtaining optimal estimates of said IMU position errors.

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