Intelligent intersection apparatus and method for network-based positioning

• US 20060234673A1
• Filed: 04/14/2005
• Published: 10/19/2006
• Est. Priority Date: 04/14/2005
• Status: Active Grant

• Current Assignee: Nokia Corporation
• Original Assignee: Nokia Corporation
• Inventors: Trux, Antoine, Sorri, Antti, Jaakkola, Jussi
• Granted Patent: US 7,577,440 B2
• Time in Patent Office: Days
• US Class Current: 455/406
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

An intelligent intersection method and apparatus for network-based positioning include defining a first cell model having a first antenna as a center point and a second cell model having a second antenna as the center point, determining first and second distances from the first and second antennas, respectively, to a mobile station. The method and apparatus define a first circle for the first cell model using the first distance as a radius and a second circle for the second cell model using the second distance as the radius. The method and apparatus further determine first and second intersection points of the first and second circles, and determine a cost function for the first intersection point and the second intersection point relative to the first and second cell models based on parameters defining each cell to select the first or the second intersection point indicative of a location of the mobile station.

Claims

1. An intelligent intersection method for network-based positioning, comprising:

defining a first cell model having a first antenna as a center point and a second cell model having a second antenna as the center point;

determining first and second distances from the first and second antennas, respectively, to a mobile station;

defining a first circle for the first cell model using the first distance as a radius of the first circle;

defining a second circle for the second cell model using the second distance as the radius of the second circle;

determining first and second intersection points of the first and second circles; and

determining a cost function for the first intersection point and the second intersection point relative to the first and second cell models based on parameters defining each cell to select the first or the second intersection point indicative of a location of the mobile station.

2. The intelligent intersection method as recited in claim 1, further comprising:

computing a first cost function component cf_cell1(I_A) of the first intersection point relative to the first cell model and comprising a distance f_A1 and a distance f_A2, as follows

cf_cell1(I_A)=f_A1(I_A)+(γ

×

f_A2(I_A))

wherein I_A is the first intersection point, the distance f_A1 is a shortest distance along the first circle from the first intersection point to a bearing of the first antenna, and the distance f_A2 is a shortest distance from the first intersection point to the first cell model, and γ

is a predetermined fixed value.

3. The intelligent intersection method as recited in claim 2, further comprising:

computing a second cost function component cf_cell2(I_A) of the first intersection point relative to the second cell model and comprising a distance f_A3 and a distance f_A4, as follows

cf_cell2(I_A)=f_A3(I_A)+(γ

×

f_A4(I_A))

wherein the distance f_A3 is a shortest distance along the second circle from the first intersection point to the antenna bearing of the second antenna, and the distance f_A4 is a shortest distance from the first intersection point to the second cell model, and γ

is the predetermined fixed value.

4. The intelligent intersection method as recited in claim 3, wherein the determining of the cost function of the first intersection point comprises adding the first and second cost function components cf_cell1(I_A) and cf_cell2(I_A), as follows

cf(I_A)=cf_cell1(I_A)+cf_cell2(I_A),

where cf(I_A) is the cost function of the first intersection point.

5. The intelligent intersection method as recited in claim 4, further comprising:

computing a first cost function component cf_cell1(I_B) of the second intersection point relative to the first cell model and comprising a distance f_B1 and a distance f_B2, as follows

cf_cell1(I_B)=f_B1(I_B)+(γ

×

f_B2(I_B))

wherein I_B is the second intersection point, the distance f_B1 is a shortest distance along the first circle from the second intersection point to the antenna bearing of the first antenna, and the distance f_B2 is a shortest distance from the second intersection point to the first cell model, and γ

is the predetermined fixed value.

6. The intelligent intersection method as recited in claim 5, further comprising:

computing a second cost function component cf_cell2(I_B) of the second intersection point relative to the second cell model and comprising a distance f_B3 and a distance f_B4, as follows

cf_cell2(I_B)=f_B3(I_B)+(γ

×

f_B4(I_B))

wherein the distance f_B3 is a shortest distance along the second circle from the second intersection point to the antenna bearing of the second antenna, and the distance f_B4 is a shortest distance from the second intersection point to the second cell model, and γ

is the predetermined fixed value.

7. The intelligent intersection method as recited in claim 6, wherein the determining of the cost function of the second intersection point comprises adding the first and second cost function components cf_cell1(I_B) and cf_cell2(I_B), as follows

cf(I_B)=cf_cell1(I_B)+cf_cell2(I_B),

where cf(I_B) is the cost function of the second intersection point.

8. The intelligent intersection method as recited in claim 7, further comprising:

selecting as the location of the mobile station the one of the first and second intersection points for which the cost function cf(I_A) or cf(I_B) yields a smaller value.

9. The intelligent intersection method as recited in claim 8, further comprising:

determining γ

during system setup by empirical means, wherein γ

is the same for cf_cell1(I_A), cf_cell2(I_A), cf_cell1(I_B), and cf_cell2(I_B).

10. The intelligent intersection method as recited in claim 1, wherein the parameters for each of the first and second cell models comprise an antenna bearing defining a main power direction of the antenna, a half power beam width, a maximum serving radius, and a back serving radius.

11. The intelligent intersection method as recited in claim 2, further comprising:

defining the distance f_A2 to be equal to zero when the first intersection point is inside the first cell model.

12. The intelligent intersection method as recited in claim 3, further comprising:

defining the distance f_A4 to be equal to zero when the first intersection point is inside the second cell model.

13. The intelligent intersection method as recited in claim 5, further comprising:

defining the distance f_B2 to be equal to zero when the second intersection point is inside the first cell model.

14. The intelligent intersection method as recited in claim 6, further comprising:

defining the distance f_B4 to be equal to zero when the second intersection point is inside the second cell model.

15. The intelligent intersection method as recited in claim 1, further comprising:

determining a half power beam width of the first cell model, φ

_HPBW1, and the half power beam width of the second cell model, φ

_HPBW2; and

determining a weight value, w_cell1, for the first and second intersection points relative to the first cell model, as follows

w_cell1=φ

_HPBW1<sup>−

1</sup>/(φ

_HPBW1<sup>−

1</sup>+φ

_HPBW2⁻

).

16. The intelligent intersection method as recited in claim 15, further comprising:

determining a weight value, w_cell2, for the first and second intersection points relative to the second cell model, as follows

w_cell2=φ

_HPBW2<sup>−

1</sup>/(φ

_HPBW1<sup>−

1</sup>+φ

_HPBW2<sup>−

1</sup>).

17. The intelligent intersection method as recited in claim 16, further comprising:

determining an angular difference, δ

_A1, between the bearing of the antenna of the first cell model and a straight line from the antenna of the first cell model to the first intersection point.

18. The intelligent intersection method as recited in claim 17, further comprising:

calculating a first cost function component f_cell1(I_A) for the first intersection point relative to the first cell model as follows

f_cell1(I_A)=w_cell1×

δ

_A1.

19. The intelligent intersection method as recited in claim 18, further comprising:

determining an angular difference, δ

_A2, between the bearing of the antenna of the second cell model and a straight line from the antenna of the second cell model to the first intersection point.

20. The intelligent intersection method as recited in claim 19, further comprising:

calculating the second cost function component f_cell2(I_A) for the first intersection point relative to the second cell model, as follows

f_cell2(I_A)=w_cell2×

δ

_A2.

21. The intelligent intersection method as recited in claim 20, wherein the determining of the cost function of the first intersection point is performed by adding the first function component f_cell1(I_A) and the second cost function component f_cell2(I_A) for the first intersection point relative to the first and second cell models as follows

f(I_A)=f_cell1(I_A)+f_cell2(I_A),

where f(I_A) is the cost function of the first intersection point.

22. The intelligent intersection method as recited in claim 21, further comprising:

determining an angular difference, δ

_B1, between the bearing of the antenna of the first cell model and a straight line from the antenna of the first cell model to the second intersection point.

23. The intelligent intersection method as recited in claim 22, further comprising:

calculating a first cost function component f_cell1(I_B) for the second intersection point relative to the first cell model as follows

f_cell1(I_B)=w_cell1×

δ

_B1.

24. The intelligent intersection method as recited in claim 23, further comprising:

determining an angular difference, δ

_B2, between the bearing of the antenna of the second cell model and a straight line from the antenna of the second cell model to the second intersection point.

25. The intelligent intersection method as recited in claim 24, further comprising:

calculating the second cost function component f_cell2(I_B) for the second intersection point relative to the second cell model, as follows

f_cell2(I_B)=w_cell2×

δ

_B2.

26. The intelligent intersection method as recited in claim 25, wherein the determining of the cost function of the second intersection point is performed by adding the first function component f_cell1(I_B) and the second cost function component f_cell2(I_B) as follows

f(I_B)=f_cell1/(I_B)+f_cell2(I_B),

where f(I_B) is the cost function of the second intersection point.

27. The intelligent intersection method as recited in claim 26, further comprising:

selecting as the location of the mobile station the one of the first and second intersection points for which the cost function f(I_A) or f(I_B) yields the smaller value.

28. An intelligent intersection method for network-based positioning, comprising:

defining a first circle for a first cell model using a first distance to a mobile station as a radius of the first circle;

defining a second circle for a second cell model using a second distance to the mobile station as the radius of the second circle;

determining first and second intersection points of the first and second circles; and

determining a cost function for the first intersection point and the second intersection point relative to the first and second cell models based on parameters defining each cell to select the first or the second intersection point indicative of a location of the mobile station.

29. An intelligent intersection apparatus for network-based positioning, comprising:

a base station controller defining a first cell model having a first antenna as a center point and a second cell model having a second antenna as the center point, determining first and second distances from the first and second antennas, respectively, to a mobile station, defining a first circle for the first cell model using the first distance as a radius of the first circle, defining a second circle for the second cell model using the second distance as the radius of the second circle; and

a location services node determining first and second intersection points of the first and second circles, and determining a cost function for the first intersection point and the second intersection point relative to the first and second cell models based on parameters defining each cell to select the first or the second intersection point indicative of a location of the mobile station.

30. An intelligent intersection apparatus for network-based positioning, comprising:

base station means for defining a first cell model having a first antenna as a center point and a second cell model having a second antenna as the center point, for determining first and second distances from the first and second antennas, respectively, to a mobile station, for defining a first circle for the first cell model using the first distance as a radius of the first circle, for defining a second circle for the second cell model using the second distance as the radius of the second circle; and

location services means for determining first and second intersection points of the first and second circles, and for determining a cost function for the first intersection point and the second intersection point relative to the first and second cell models based on parameters defining each cell to select the first or the second intersection point indicative of a location of the mobile station.