Method and apparatus for determining accuracy of the estimated location for a target in a wireless system

• US 7,970,575 B2
• Filed: 12/31/2008
• Issued: 06/28/2011
• Est. Priority Date: 04/20/2007
• Status: Active Grant

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Hsyu, Ming-Chun, Chen, Chao-Nan, Tsuei, Wen
• Primary Examiner(s): Wachsman; Hal D
• Application Number:
  US12/346,878
• Publication Number:
  US 20090112517A1
• Time in Patent Office: 909 Days
• Field of Search: 702/150, 702/181, 702/189
• US Class Current: 702/150
• CPC Class Codes: G01S 5/021 Calibration, monitoring or correction G01S5/0252 takes precedence
• CPC Class Codes: G01S 5/0244 Accuracy or reliability of position solution or of measurements contributing thereto
• CPC Class Codes: G01S 5/02521 using a radio-map
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence

Abstract

A method for determining the accuracy of the estimated position for a target device in a wireless system includes the computation of a confidence index. In the online location determining phase, after knowing the observations of the radio signal for a target device, the target device'"'"'s probability distribution of location and its motion model are combined to calculate the position uncertainty, thereby giving the confidence index of this location estimate. The invention determines the location probability distribution, and calculates the uncertainty of the location probability distribution and the possible maximum uncertainty under the current situation. Based on these uncertainties, this invention determines the confidence index of the radio signal. The confidence may be regarded as a quantity that the location uncertainty can be excluded in the location prediction.

Claims

1. A method for determining accuracy of an estimated location of a target device in a wireless system by using an apparatus having computing and storage devices, said method comprising the steps of:

determining a location probability density function of said target device using said computing device based on a location probability model stored in said storage device, said location probability model indicating the location probability density function of said target device when a received radio signal from said target device is known;

calculating an uncertainty at a current estimated location and a possible maximum uncertainty using said computing device based on radio signals received by said target device according to said location probability density function; and

calculating a confidence index of said current estimated location using said computing device based on said uncertainty and said maximum uncertainty by computing an uncertainty quantity defined as a ratio of said uncertainty to said maximum uncertainty and computing said confidence index as a function of said uncertainty quantity;

wherein said confidence index of said current estimated location determines the accuracy of said current estimated location with higher confidence index representing higher accuracy.

2. The method as claimed in claim 1, wherein said confidence index depends on the quantity of said uncertainty of said current estimated location that is excluded from location prediction for said target device.

3. The method as claimed in claim 1, wherein said location probability density function is a conditional probability density function p(q_t|{o_k}_k=1^t), where q_t is a location at time t, o_k is a radio signal received by said target device at time k which has a time range from 1 to t, and {o_k}_k=1^t are said radio signals received by said target device.

4. The method as claimed in claim 3, wherein said conditional probability density function p(q_t|{o_k}_k=1^t) is determined by computing

5. The method as claimed in claim 3, wherein said uncertainty is calculated from a self-contained information function of said location probability density function.

6. The method as claimed in claim 5, wherein said p(q_t|{o_k}_k=1^t) is determined from a transition probability between two locations and the probability of receiving said radio signals {o_k}_k=1^t by applying a Hidden Markov model.

7. The method as claimed in claim 6, wherein said self-contained information function is defined as U(Q_t|{o_k}_k=1^t) obtained through the following expression:

8. The method as claimed in claim 7, wherein said maximum uncertainty occurs when the probabilities of possible locations according to said location probability density function are identical, and said maximum uncertainty has a maximum entropy.

9. The method as claimed in claim 8, wherein said maximum entropy is log₂(|Q_t|).

10. The method as claimed in claim 9, wherein said confidence index is a function of H(Q_t|{o_k}_k=1^t) and log₂(|Q_t|).

11. An apparatus having computing and storage devices configured for determining accuracy of an estimated location of a target device in a wireless system, said apparatus comprising:

a probability density function generator configured with said computing device for generating a location probability density function for said target device based on a location probability model stored in said storage device, said location probability model indicating the location probability density function of said target device when a received radio signal from said target device is known;

an uncertainty computation module configured with said computing device for calculating an uncertainty at a current estimated location and a possible maximum uncertainty based on radio signals received by said target device according to said location probability density function; and

a confidence index computing module configured with said computing device for calculating a confidence index of said current estimated location based on said uncertainty and said maximum uncertainty by computing an uncertainty quantity defined as a ratio of said uncertainty to said maximum uncertainty and computing said confidence index as a function of said uncertainty quantity;

wherein said confidence index of said current estimated location determines the accuracy of said current estimated location with higher confidence index representing higher accuracy.

12. The apparatus as claimed in claim 11, wherein said confidence index depends on the quantity of said uncertainty of said current estimated location that is excluded from location prediction for said target device.

13. The apparatus as claimed in claim 11, wherein said location probability density function is a conditional probability density function p(q_t|{o_k}_k=1^t), where q_t is a location at time t, o_k is a radio signal received by said target device at time k which has a time range from 1 to t, and {o_k}_k=1^t are said radio signals received by said target device.

14. The apparatus as claimed in claim 13, wherein said conditional probability density function p(q_t|{o_k}_k=1^t) is determined by computing

15. The apparatus as claimed in claim 13, wherein said uncertainty is calculated from a self-contained information function of said location probability density function.

16. The apparatus as claimed in claim 15, wherein said p(q_t|{o_k}_k=1^t) is determined from a transition probability between two locations and the probability of receiving said radio signals {o_k}_k=1^t by applying a Hidden Markov model.

17. The apparatus as claimed in claim 16, wherein said self-contained information function is defined as U(Q_t|{o_k}_k=1^t) obtained through the following expression:

18. The apparatus as claimed in claim 17, wherein said maximum uncertainty occurs when the probabilities of possible locations according to said location probability density function are identical, and said maximum uncertainty has a maximum entropy.

19. The apparatus as claimed in claim 18, wherein said maximum entropy is log₂(|Q_t|).

20. The apparatus as claimed in claim 19, wherein said confidence index is a function of H(Q_t|{o_k}_k=1^t) and log₂(|Q_t|).