System and method for integrated navigation with wireless dynamic online models

Patent metadata

Field	Value
Publication number	US-10132915-B2
Application number	US-201414916908-A
Country	US
Kind code	B2
Filing date	Sep 5, 2014
Priority date	Sep 6, 2013
Publication date	Nov 20, 2018
Grant date	Nov 20, 2018

Abstract

The present disclosure relates to a system and method for integrating online, dynamic wireless system modeling with a navigation solution. The building of wireless dynamic online models for wireless positioning does not require pre-existing information such as pre-surveys and is capable of providing relatively better accuracy. Integration of the wireless positioning using dynamic online models with other navigation systems/solutions is proposed whereby the other navigation system/solution can benefit and enhance the building of wireless dynamic online models. In addition, the wireless dynamic online models can be optimally integrated with the other navigation system/solution for enhanced positioning performance.

First claim

The embodiments in which an exclusive property or privilege is claimed are defined as follows:

1. A method for integrating online, dynamic wireless system modeling with a navigation solution about at least one wireless-enabled device, wherein the method builds an automatic, online, dynamic model configured to predict the received signal strength of a signal transmitted by at least one transceiver means at any location within a wireless network area, wherein the wireless network has an infrastructure, wherein the at least one transceiver means is configured to transmit a wireless signal comprising a power pattern, wherein the at least one transceiver means constitutes the infrastructure of the wireless network, wherein the at least one device is configured to receive the signal(s) from the at least one transceiver means and wherein the at least one device comprises inertial sensors, the method comprising:
receiving the power pattern(s) transmitted from the at least one transceiver means, wherein the power pattern comprises:
i. information that identifies the at least one transmitting transceiver means, and information that identifies any other transceiver means in the area and visible by the at least one transmitting transceiver means,
ii. power information for a signal transmitted by the at least one transmitting transceiver means, and
iii. received signal strength information of signals transmitted by the any other transceiver means in the area and visible by the at least one transmitting transceiver means;

and further comprising:
a. processing information that identifies the at least one transceiver means to locate the at least one transceiver means,
b. building the automatic, online, dynamic model configured to predict the received signal strength of a signal transmitted by the at least one transceiver means at any location within the area, and
c. integrating the model with the navigation solution, wherein the navigation solution is based at least in part on output of the inertial sensors.

2. The method of claim 1 , wherein integrating the model with the navigation solution comprises any one or any combination of:
a. using the wireless model to calculate a position of the at least one device, and integrating said position with the navigation solution;
b. using the wireless model to calculate a position of the at least one device, integrating said position with the navigation solution, and calculating an accuracy measure of the at least one device position, wherein the accuracy measure is utilized when the position is integrated with the navigation solution;
c. updating the navigation solution using the predicted received signal strength from the wireless model or a distance calculated from the predicted received signal strength between the at least one device and the at least one transceiver;
d. updating the navigation solution using the predicted received signal strength from the wireless model or a distance calculated from the predicted received signal strength between the at least one device and the at least one transceiver, and calculating an accuracy measure of the predicted received signal strength from the wireless model or the distance calculated from said predicted received signal strength, wherein the accuracy measure is utilized when the navigation solution is updated; and
e. utilizing the navigation solution for at least one of:
i. assisting in the building of the wireless model; and
ii. verifying and correct the built wireless model.

3. The method of claim 1 , wherein the wireless model is one of the following:
a. an online propagation model of the at least one transceiver means, wherein the propagation model relates the received signal strength from the at least one transceiver means to a distance from the at least one transceiver means,
b. an online power profile of the at least one transceiver means, wherein the power profile relates the received signal strength from the at least one transceiver means to a location in the wireless network area, and
c. a combination of the propagation model and the online power profile of the at least one transceiver means.

4. The method of claim 3 , wherein the wireless models are built using at least one of:
a. an adaptive, calibrated best-fit mathematical formula;
b. an adaptive, calibrated conditional probabilistic approach; and
c. a combination of an adaptive, calibrated hybrid approach that combines a best fit mathematical model and a conditional probabilistic approach.

5. The method of claim 1 , wherein the wireless models undergo at least one of:
a. online, automatic, dynamic, and adaptive verification and correction; and
b. online, automatic, dynamic, and adaptive verification and correction, wherein the verification and the correction of the models occurs periodically.

6. The method of claim 1 , wherein the method further comprises at least one of:
a. calculating an accuracy measure of the predicted signal strength; and
b. calculating an accuracy measure of the predicted signal strength, wherein the accuracy measure is calculated by:
i. calculating a conditional probability of the signal strength conditioned on, or given, the information in the power patterns,
ii. calculating a variance of the conditional probability, and
iii. converting the variance into an accuracy measure of the predicted received signal strength.

7. The method of claim 1 , wherein the method further comprises at least one of:
a. determining the location(s) of the at least one transceiver means by at least one of:
i. using a table containing the location(s) of the at least one transceiver means indexed by the information that identifies the at least one transceiver means; and
ii. encoding the location(s) of the at least one transceiver means in the power patterns transmitted by the at least one transceiver means;

b. calculating the location(s) of the at least one transceiver means; and
c. utilizing the navigation solution to determine the location(s) of the at least one transceiver means or assist in the determination of the locations(s) of the at least one transceiver means.

8. The method of any one of claim 1 , 2 , 3 , 5 , 6 or 7 , wherein the power patterns transmitted by the at least one transceiver means are broadcasted wirelessly or transmitted through a wired network to the at least one processor.

9. The method of claim 1 wherein the at least one device communicates with the at least one processor through:
a. wireless communication,
b. wired communication, or
c. by embedding the at least one processor inside the at least one wireless-enabled device in a single device.

10. The method of claim 1 , wherein the at least one processor is further capable of ranking the at least one transceiver means.

11. The method of claim 10 , wherein the ranking of the at least one transceiver means is achieved by:
a. obtaining a power profile of the at least one transceiver means,
b. merging all power profiles of all the at least one transceiver means to construct a radio-map of the area,
c. applying a principle component analysis to the constructed radio map, and
d. ranking the at least one transceiver means according to the positioning discrimination significance of each.

12. The method of claim 11 , wherein the ranking of the plurality of transceivers means in the wireless area network is calculated by:
a. obtaining the principle component analysis transformation matrix, wherein the matrix comprises columns and each column has a number of elements equal to the number of the plurality of transceivers means in the wireless area network, and
b. ranking, for each column in the principle co

Assignees

• Invensense Inc

Inventors

• Georgy Jacques
• Syed Zainab
• Goodall Christopher

Classifications

• G01S5/021

  Calibration, monitoring or correction (G01S5/0252 takes precedence) · CPC title

• G01S5/0263 Primary

  by combining or switching between positions derived from two or more separate positioning systems · CPC title

• G01S5/0242

  Determining the position of transmitters to be subsequently used in positioning (G01S5/0289 takes precedence) · CPC title

• G01S19/45

  by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement · CPC title

• G01S5/0252

  Radio frequency fingerprinting · CPC title