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Position estimation for navigation devices

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Title: Position estimation for navigation devices.
Abstract: A method of providing position estimation with a navigation device comprises periodically recording magnetic field strength of an area substantially surrounding a navigation device as a user of the navigation device traverses a select pathway. The method combines the recorded magnetic field strength with measurements from at least a dead reckoning portion of the navigation device to provide position estimates along the select pathway. The method further corrects each of the position estimates from a starting position on the select pathway, where each of the corrected position estimates have an error value below one or more previous position estimates and any intervening positions between each of the one or more previous position estimates and the starting position, with the error value corresponding to an error threshold based on the previous position estimates. ...


Browse recent Honeywell International, Inc. patents - Morristown, NJ, US
Inventors: Tom Judd, Bruce Graham, Toan Vu
USPTO Applicaton #: #20120173139 - Class: 701466 (USPTO) - 07/05/12 - Class 701 


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The Patent Description & Claims data below is from USPTO Patent Application 20120173139, Position estimation for navigation devices.

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CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of pending U.S. application Ser. No. 12/059,865 entitled “POSITION ESTIMATION FOR NAVIGATION DEVICES,” filed Mar. 31, 2008, which is incorporated herein by reference.

GOVERNMENT INTEREST STATEMENT

The U.S. Government may have certain rights in the present invention under contract No. HDTRA-06-6-C-0058, subcontract No. CHI-06022-001 as awarded by the Defense Threat Reduction Agency.

BACKGROUND

Reliable navigation systems and devices have always been essential for estimating both distance traveled and position. For example, early navigating was accomplished with “deduced” or “dead” reckoning. In dead-reckoning, a navigator finds a current position by measuring the course and distance the navigator has moved from some known point. Starting from the known point, the navigator measures out a course and distance from that point. Each ending position will be the starting point for the course-and-distance measurement. In order for this method to work, the navigator needs a way to measure a course and a way to measure the distance traveled. The course is measured by a magnetic compass. In pedestrian dead reckoning, the distance is the size of a single step. A position estimate is derived by the integration of distance and direction over a sequence of steps. This type of navigation, however, is highly prone to errors, which when compounded can lead to highly inaccurate position and distance estimates.

In more advanced navigation systems, such as an inertial navigation system (INS), positional errors can accumulate over time. For example, any navigation performed in areas where satellite or radar tracking measurements are inaccessible or restrictive (such as areas where global positioning system, or GPS, measurements are “denied”) is susceptible to the accumulation of similar positional errors. Moreover, in the dead-reckoning methods discussed above, these positional errors accumulate based on the distance traveled. There is a need in the art for improvements in position estimation for navigation devices.

SUMMARY

The following specification provides for at least one method of position estimation for navigation devices using sensor data correlation. This summary is made by way of example and not by way of limitation. It is merely provided to aid the reader in understanding some aspects of at least one embodiment described in the following specification.

Particularly, in one embodiment, a method of providing position estimation with a navigation device comprises periodically recording magnetic field strength of an area substantially surrounding a navigation device as a user of the navigation device traverses a select pathway. The method combines the recorded magnetic field strength with measurements from at least a dead reckoning portion of the navigation device to provide position estimates along the select pathway. The method further corrects each of the position estimates from a starting position on the select pathway, where each of the corrected position estimates have an error value below one or more previous position estimates and any intervening positions between each of the one or more previous position estimates and the starting position, with the error value corresponding to an error threshold based on the previous position estimates.

DRAWINGS

These and other features, aspects, and advantages are better understood with regard to the following description, appended claims, and accompanying drawings where:

FIG. 1 is a block diagram of a navigation device;

FIGS. 2A and 2B are traversing diagrams of navigating in a select pathway;

FIG. 3A is a traversing diagram of navigating in a select pathway prior to position correction;

FIG. 3B is a traversing diagram of navigating in the select pathway of FIG. 3A after position correction;

FIG. 4A is a traversing diagram of a select pathway with at least one marked position before sensor data correlation at a selected position;

FIG. 4B is a traversing diagram of navigating in a select pathway showing one or more positions that correlate with the marked position of FIG. 4A;

FIG. 4C is a traversing diagram of navigating in the select pathway of FIG. 4B after the correlated positions have been corrected;

FIG. 5A is a traversing diagram of navigating in a select pathway using a navigation device indicating the positions which are correlated;

FIGS. 5C is the azimuth data and 5B is the calculated correlation function diagram from the navigation device of FIG. 5A;

FIG. 6A is a traversing diagram of navigating in a select pathway using a navigation device having at least one marked position and one or more correlated positions;

FIGS. 6B and 6C are calculated correlation data diagrams for sensor data channels from the navigation device of FIG. 6A;

FIG. 7 is a diagram in graphical form illustrating product correlation as provided by the correlation data of FIGS. 6B and 6C;

FIG. 8 is a flow diagram of a method for providing position correction in a navigation device;

FIG. 9 is a flow diagram of a method of correlating position measurements in a navigation device;

FIG. 10 is a flow diagram of a method of qualifying navigation data from the navigation device of FIG. 9; and

FIG. 11 is a flow diagram of a method of correlating position measurements in a navigation device.

Like reference characters denote like elements throughout the figures and text of the specification.

DETAILED DESCRIPTION

Embodiments disclosed herein relate to position estimation for navigation devices using sensor data correlation. For example, at least one navigation device discussed herein substantially reduces positioning errors when the device recognizes that a user of the device is at a previous position. In one implementation, the navigation device discussed herein informs the user that a track crossing event has occurred based on the correlation of accumulated sensor data. Moreover, this event occurrence can be determined manually by the user or automatically detected by the sensors within the navigation device. For example, each track crossing event is detected at recognizable corners, intersections, or bottlenecks found inside a building or along a constrained (that is, a select) pathway. In one embodiment, a laser range-finder or at least one sonar-sounding sensor is coupled to the navigation device to record a characteristic “fingerprint” of each track crossing the user encounters while traversing a select pathway. The device is configurable to automatically and continuously mark likely track crossing points along the select pathway (for example, the device collects tracking data and provides an indication when a current record matches a previously-encountered region). As discussed in further detail below, the device is configurable to adjust and correct positional errors for each of the track crossings detected.

In at least one embodiment, a dead-reckoning (DR) navigation device comprises one or more inertial sensors and one or more magnetic sensors operable to obtain estimates of displacement from a starting point. The track correlation and position recognition discussed herein substantially reduces the accumulated positional errors. For example, as the user travels indoors down halls or corridors, or outdoors along trails and streets, positional corrections can be applied to current and previous position measurements, and continuously “back-propagated” over a history of position estimates between the first and second times the user reaches the same spot. In one implementation, track positions are stored in discrete steps, and the device assigns a correction to each track position by dividing the total error by the number of steps in the interval.

The position estimation methods disclosed herein will not require any additional sensors or communications infrastructure along the select pathways discussed below. For example, existing DR sensors can be used from the DR navigation device. In one embodiment, the DR navigation device uses magnetic sensors for compassing and accelerometers for step counting. Moreover, a processing unit on the DR navigation device is configured to perform the automatic track-crossing recognition and processing based on magnetic field strength measurements of an area substantially surrounding the DR navigation device.

FIG. 1 is an embodiment of a navigation system 100 (for example, a personal navigation system operable in an enclosed environment). The system 100 comprises a navigation device 102 and an output terminal 104 communicatively coupled to the navigation device 102 through an output interface 118. In one embodiment, the output interface 118 further comprises a wireless communications transceiver 119. The navigation device 102 comprises a processing unit 106, a sensor module 108, and a power block 120 that provides electrical power to the navigation device 102 and, in one implementation, the output terminal 104. In the example embodiment of FIG. 1, the navigation device 102 comprises an optional global positioning system (GPS) receiver 114 in operative communication with the processing unit 106 and an optional attachment interface 116 communicatively coupled to the processing unit 106. In one embodiment, the optional attachment interface 116 receives navigation input data (for example, from a manual marking device or the like coupled to the optional attachment interface 116 in order to record a characteristic fingerprint of the track over which a user travels). In the example embodiment of FIG. 1, the sensor module 108 comprises at least a portion of the navigation device 102 operable as a dead reckoning module. In the same embodiment, the output terminal 104 provides position estimation data to a user of the navigation device 100 (for example, the position estimation data processed by the navigation device 102). In this same embodiment, the dead reckoning portion of the navigation device 102 is operable within a sensor measurement range as indicated to the user.

The sensor module 108 comprises one or more accelerometers 109 and one or more magnetometers 110. In one implementation, the sensor module 108 further comprises one or more gyroscopes 111 and a barometric altimeter 112. It is understood that the sensor module 108 is capable of accommodating any appropriate number and types of navigational sensors and sensor blocks operable to receive sensor input data (for example, one or more of the accelerometers 109, the magnetometers 110, the gyroscopes 111, the barometric altimeter 112, and the like) in a single sensor module 108. In the example embodiment of FIG. 1, the processing unit 106 comprises at least one of a microprocessor, a microcontroller, a field-programmable gate array (FPGA), a field-programmable object array (FPOA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC). In one implementation, the processing unit 106 further comprises a memory block 107. The memory block 107 records at least each of the recognized track crossings measured by the sensor module 108.

In operation, the sensor module 108 provides position estimates based on magnetic field strength and heading data (for example, azimuth data). In one embodiment, the azimuth data is provided by the dead reckoning portion of the sensor module 108. The processing unit 106 records the position estimates along with the magnetic field measured by the sensor module 108 of an area substantially surrounding a user of the navigation device 102. The processing unit 106 measures a track crossing based on a comparison of the magnetic field strength at a current position and one or more previous position estimates. As discussed in further detail below with respect to FIGS. 4A to 4C, for each measured track crossing, the processing unit 106 aligns the current position with the one or more previous position estimates and adjusts an accumulation of measurement error below an error threshold based on the one or more previous position estimates. In the example embodiment of FIG. 1, the processing unit 106 corrects any intervening positions and error estimates between the current position and the one or more previous position estimates, as discussed in further detail below.

In one embodiment, the navigation device 102 comprises at least three magnetometers 110 to provide the heading data within the surrounding magnetic field in at least three orientations. Further, the navigation device 102 comprises at least three accelerometers 109 for step counting and the estimation of vertical in three axes for movements in at least three dimensions. The position estimation performed by the navigation device 102 provides at least one method of correction for position estimates based on at least an error threshold. For example, the sensor module 108 is operable to continually measure the azimuth data from the at least three magnetometers 110 on a sensor channel. Moreover, the sensor module 108 is further operable to provide the position estimates to the processing unit 106. In the example embodiment of FIG. 1, the position estimates are iteratively adjusted based on the error threshold, as discussed in further detail below with respect to FIGS. 5A to 5C. In one implementation, the processing unit 106 automatically recognizes the measured track crossings by correlating the magnetic field strength and the heading data between the current position and the one or more previous position estimates. In this same implementation, the processing unit 106 qualifies the current position based on correlation threshold criteria for the sensor module 108 (discussed in further detail below with respect to FIG. 10).

FIGS. 2A and 2B are traversing diagrams of navigating in a select pathway. In the example embodiments of FIGS. 2A and 2B, a navigation device 202 (representative of the navigation device 102 of FIG. 1) is worn by a user. The user marks potential track crossings using the navigation device 102. In one implementation, the user provides a marking signal from one of a manual marking device, a push button device, or the like. The next time the user crosses through the same position, the user marks the position a second time. For example, in FIG. 2A, the user having the navigation device 202 traverses along three sides of a path 204 that is 25 meters square, starting from the position labeled ‘1’, and proceeding around to a position ‘4’. The track path 204 (labeled as “DT” in FIG. 2A) will be 75 meters. Moreover, a straight line distance 206 (labeled as “DS” in FIG. 2A) between the position 1 and the position 4 is 25 meters.

In one implementation, a measure of the accumulated error between positions 1 and 4 along the select pathway comprises two distances: the first is the straight line distance “DS” between the two positions, and the second is the length of the path traveled “DT” between the two positions ‘1’ and ‘4’. A positional error measure E is provided below in Equation 1, further expressed as a percent in Equation 2 below.

E=DS/DT   (Equation 2)

E=100*(DS/DT)%   (Equation 2)

In the example embodiment of FIG. 2A, the positional error is 25 m/75 m, or 0.33 (from Equation 1), or 33% (Equation 2). The select pathway depicted in FIG. 2B illustrates the user traversing around a square path 208 back to the starting position 1. As shown in FIG. 2B, positional errors accumulate in a position estimate provided by the navigation device 202, resulting in the navigation device 202 directing the user along a path 210 to the position 1′ instead of 1. For example, if position 1 and position 1′ are three meters apart, then the measure of error is 3 m/100 m, or 0.03 (3%). For each position marking event, all marks that lie outside a error threshold range are disregarded, and marks at or below the error threshold are ranked according to the error measure in Equation 1.



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stats Patent Info
Application #
US 20120173139 A1
Publish Date
07/05/2012
Document #
12971265
File Date
12/17/2010
USPTO Class
701466
Other USPTO Classes
International Class
01C21/00
Drawings
12



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