Apparatus and method for measuring the accurate position of moving objects in an indoor environment

• US 7,761,233 B2
• Filed: 06/30/2006
• Issued: 07/20/2010
• Est. Priority Date: 06/30/2006
• Status: Active Grant

• Current Assignee: Generac Power Systems Incorporated (Generac Holdings Incorporated)
• Original Assignee: International Business Machines Corporation
• Inventors: Weiss, Beat, Schott, Wolfgang Hans, Furrer, Simeon
• Primary Examiner(s): Black; Thomas G
• Assistant Examiner(s): Chen; Shelley
• Application Number:
  US11/428,019
• Publication Number:
  US 20080004796A1
• Time in Patent Office: 1,481 Days
• Field of Search: 701/201
• US Class Current: 701/221
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence

Abstract

An apparatus and method is disclosed for efficiently sensing and tracking objects in an indoor environment by simultaneously measuring the object movement with an inertial navigation system and a reference location positioning system. By combining the measurements obtained with accelerometers, gyroscopes, angle estimators and the reference system using an extended Kalman filter based approach, a position estimate is obtained with high reliability and precision accuracy. Improvement in performance is obtained by the incorporation of dynamic mode switching and forward-backward smoothing in the location position estimator.

Claims

1. An apparatus for providing accurate position of a moving object in an indoor environment, comprising:

a Reference Positioning System (RPS);

an Inertial Measurement Unit (IMU) installed on said moving object;

a Coordinate Transformer (COT) coupled to the outputs of said IMU; and

a Location Position Estimator (LPE) coupled to the outputs of said RPS and said COT, wherein said LPE comprises, for each dimension of the position coordinates;

a forward Kalman Filter having one input coupled to the output from the RPS for receiving the reference position signal and a second input coupled to the output from said COT for obtaining the rotated accelerometer measurements;

a recording unit having one input coupled to the output from the RPS and a second unit coupled to the output from said COT;

a motion and reference detector having one input coupled to the output from the RPS and a second input coupled to the output from said COT;

a backward Kalman Filter having its inputs connected to the outputs of said recording unit;

a smoothing unit having one input coupled to an output of said forward Kalman Filter and a second input connected to the output of said backward Kalman Filter; and

a control unit coupled to the output of said motion and reference detector, said control unit controlling the operation of said forward Kalman Filter, said backward Kalman Filter, and said smoothing unit.

2. An apparatus for providing accurate position of a moving object in an indoor environment, as claimed in claim 1, wherein said IMU comprising:

one or more gyroscopic units, and

one or more accelerometer units.

3. An apparatus for providing accurate position of a moving object in an indoor environment, as claimed in claim 1, wherein said COT comprising:

an angle estimator coupled to the outputs from the IMU, and

a rotation unit coupled to the outputs from said IMU and the output of said angle estimator.

4. An apparatus for providing accurate position of a moving object in an indoor environment as claimed in claim 1, wherein said forward Kalman Filter comprising:

a process and measurement model that models the movement of the object along an axis of the target co-ordinate system, the relation between acceleration and position, and accelerometer imperfections; and

a set of Kalman Filter gains whose setting is derived from the covariance matrix of the state-vector estimation error.

5. An apparatus for providing accurate position of a moving object in an indoor environment as claimed in claim 4, wherein:

said process and measurement model comprises four integrators providing estimates for the position, velocity, and acceleration of the object, and for the accelerometer bias; and

said set of Kalman Filter gains comprises eight gains.

6. An apparatus for providing accurate position of a moving object in an indoor environment as claimed in claim 1, wherein said backward Kalman Filter comprising

a filter structure as defined for said forward Kalman Filter;

and

means for backward processing in time the recorded said rotated accelerometer measurements and said reference position signal, starting with the acceleration and velocity estimates set to zero in said backward Kalman Filter.

7. An apparatus for providing accurate position of a moving object as claimed in claim 1, wherein said smoothing unit combines the estimates of said forward and backward Kalman Filters by weighting the estimates in accordance to the covariance matrices of the corresponding state vector estimation error.

8. An apparatus for providing accurate position of a moving object as claimed in claim 1, wherein said motion and reference detector comprising

a sampling device for sampling the absolute value of said rotated accelerometer measurements;

an averaging device for averaging a given number of consecutive samples; and

a motion detecting device for identifying motion based on said average value being above a defined threshold.

9. A method for accurately determining the position of a moving object in an indoor environment using a combination of an Inertial Measurement Unit (IMU) and a Reference Positioning System (RPS), comprising the steps of:

obtaining reference position data from said RPS;

obtaining additional data on the moving object from said IMU; and

estimating the position of the moving object from the data obtained from the RPS and the IMU, wherein the position estimation is performed by the steps of;

detecting first event “

object motion status”

based on said rotated accelerometer measurements, and detecting second event “

presence or absence of said reference position signal”

;

switching between modes of operation depending on said first event and said second event according to;

if object is in motion and said reference position signal is present, then said forward Kalman Filter provides estimates for position, acceleration, and velocity of object, and an estimate for accelerometer bias based on said rotated accelerometer measurements and said reference position signal;

if object is in motion and said reference position signal is absent, then said forward Kalman Filter is reconfigured to reflect absence of reference position measurements in the filter and to freeze the estimate of accelerometer bias to the present value, and then provide estimates for determining position, acceleration, and velocity of object;

if object is in motion, then said rotated acceleration measurements, said reference positioning signal, and said first and second events are recorded for performing forward-backward smoothing at the next stop of the object;

if object is stationary, then the acceleration and velocity estimates in said forward Kalman Filter are set to zero, and said forward Kalman Filter is reconfigured to reflect the stationary object status in the filter; and

said forward Kalman Filter, said backward Kalman Filter, and said smoothing unit provide smoothed position estimates by performing forward-backward smoothing based on said recorded rotated acceleration measurements and reference position signal.

10. A method for accurately determining the position of a moving object in an indoor environment as claimed in claim 9, wherein said additional data is determined by the steps of:

estimating angular position of said IMU in body-fixed co-ordinate system based on angular velocity measurements obtained from said IMU,

obtaining accelerometer measurements from said IMU along the x-and y-axis of body-fixed co-ordinate system, and

transforming acceleration measurements into target co-ordinate system using the angular position estimate.

11. A method for accurately determining the position of a moving object in an indoor environment as claimed in claim 9, wherein said position estimation is performed by applying a set of forward Kalman Filters to determine the coordinates of the position.