Systems and methods for estimating a position of a receiver

1. A method for estimating a position of a mobile device using information from two positioning technologies wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology;

determining a second position estimate for the mobile device using a second positioning technology;

determining a first uncertainty metric that represents uncertainty of the first position estimate;

determining a second uncertainty metric that represents uncertainty of the second position estimate;

determining a first variance using the first uncertainty metric;

determining a second variance using the second uncertainty metric;

determining a total variance using the first variance and the second variance;

determining a first ratio of the first variance to the total variance;

determining a second ratio of the second variance to the total variance;

determining a first weight using the first ratio;

determining a second weight using the second ratio;

applying the first weight to the first position estimate to generate a first weighted position estimate;

applying the second weight to the second position estimate to generate a second weighted position estimate, and

determining a final position estimate for the mobile device using an average of at least the first weighted position estimate and the second weighted position estimate.

2. The method of claim 1 , wherein the total variance comprises a sum of a plurality of variances that include the first variance and the second variance.

3. A method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology;

determining a second position estimate for the mobile device using a second positioning technology;

determining a first uncertainty metric that represents uncertainty of the first position estimate;

determining a second uncertainty metric that represents uncertainty of the second position estimate;

determining a first corrected uncertainty metric by inputting the first uncertainty metric into a first mapping function;

determining a second corrected uncertainty metric by inputting the second uncertainty metric into a second mapping function;

determining a first weight using the first corrected uncertainty metric;

determining a second weight using the second corrected uncertainty metric;

applying the first weight to the first position estimate to generate a first weighted position estimate; and

applying the second weight to the second position estimate to generate a second weighted position estimate;

determining a final position estimate for the mobile device using a combination of the first weighted position estimate and the second weighted position estimate.

4. The method of claim 3 , wherein:

the first mapping function multiplies the first uncertainty metric by a first multiplied coefficient to produce a first product, and sums the first product and a first added coefficient to produce the first corrected uncertainty metric; and

the second mapping function multiplies the second uncertainty metric by a second multiplied coefficient to produce a second product, and sums the second product and a second added coefficient to produce the second corrected uncertainty metric.

5. A method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology; and

using a second positioning technology to:

initialize a hypothesis grid, where each hypothesis in the grid has an assumed location and a weight;

for each hypothesis in the grid, recalculate the weight of that hypothesis based on a respective distance between the assumed location and the first position estimate; and

normalizing the recalculated weights such that the sum of all of the recalculated weights is equal to one;

determine a final position estimate for the mobile device using the normalized weights.

6. The method of claim 5 , wherein the final position estimate is determined using the normalized weights by using the normalized weights as a confidence factor or measurement noise estimate in a Kalman or particle filter.

7. The method of claim 5 , wherein for each particular hypothesis in the grid, the recalculated weight of the particular hypothesis is determined using (a) the weight of the particular hypothesis and (b) a multiplier that is determined using an exponential function of a negative value, wherein the value is determined by dividing (i) a square of the respective distance between the assumed location of the particular hypothesis and the first position estimate by (ii) a variance of the first position estimate.

8. The method of claim 5 , wherein for each particular hypothesis in the grid, the recalculated weight of the particular hypothesis is determined using (a) the weight of the particular hypothesis and (b) a multiplier that is (i) larger than each other multiplier used to determine a respective recalculated weight of a respective hypothesis in the grid that has a respective assumed location that is further away from the first position estimate than the assumed location of the particular hypothesis, and (ii) smaller than each other multiplier used to determine a respective recalculated weight of a respective hypothesis in the grid that has a respective assumed location that is closer to the first position estimate than the assumed location of the particular hypothesis.

9. A method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

for each transmitter in a transmitter network of a first positioning technology, estimating a pseudorange between an unknown location of the mobile device and a known location of that transmitter;

determining an estimated position of the unknown location of the mobile device using a second positioning technology;

determining an uncertainty metric of the estimated position;

for each transmitter in the transmitter network, determining a distance between the estimated position and the known location of that transmitter;

for each transmitter in the transmitter network, determining a pseudorange error as the difference between the estimated pseudorange for that transmitter and the determined distance for that transmitter;

determining a scale factor that is based on the uncertainty metric;

for each transmitter in the transmitter network, determining a pseudorange correction for that transmitter by scaling the determined pseudorange error for that transmitter using the scale factor; and

for each transmitter in the transmitter network, determining a corrected pseudorange for that transmitter as the difference between the estimated pseudorange for that transmitter and the pseudorange correction for that transmitter.

10. The method of claim 9 , wherein the method comprises:

determining a final position estimate for the mobile device using the corrected pseudoranges.

11. One or more non-transitory machine-readable media embodying program instructions that, when executed by one or more machines, cause the one or more machines to implement a method for estimating a position of a mobile device using information from two positioning technologies wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology;

determining a second position estimate for the mobile device using a second positioning technology;

determining a first uncertainty metric that represents uncertainty of the first position estimate;

determining a second uncertainty metric that represents uncertainty of the second position estimate;

determining a first variance using the first uncertainty metric;

determining a second variance using the second uncertainty metric;

determining a total variance using the first variance and the second variance;

determining a first ratio of the first variance to the total variance;

determining a second ratio of the second variance to the total variance;

determining a first weight using the first ratio;

determining a second weight using the second ratio;

applying the first weight to the first position estimate to generate a first weighted position estimate;

applying the second weight to the second position estimate to generate a second weighted position estimate, and

determining a final position estimate for the mobile device using an average of at least the first weighted position estimate and the second weighted position estimate.

12. The one or more non-transitory machine-readable media of claim 11 , wherein the total variance comprises a sum of a plurality of variances that include the first variance and the second variance.

13. One or more non-transitory machine-readable media embodying program instructions that, when executed by one or more machines, cause the one or more machines to implement a method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology;

determining a second position estimate for the mobile device using a second positioning technology;

determining a first uncertainty metric that represents uncertainty of the first position estimate;

determining a second uncertainty metric that represents uncertainty of the second position estimate;

determining a first corrected uncertainty metric by inputting the first uncertainty metric into a first mapping function;

determining a second corrected uncertainty metric by inputting the second uncertainty metric into a second mapping function;

determining a first weight using the first corrected uncertainty metric;

determining a second weight using the second corrected uncertainty metric;

applying the first weight to the first position estimate to generate a first weighted position estimate; and

applying the second weight to the second position estimate to generate a second weighted position estimate;

determining a final position estimate for the mobile device using a combination of the first weighted position estimate and the second weighted position estimate.

14. The one or more non-transitory machine-readable media of claim 13 , wherein:

the first mapping function multiplies the first uncertainty metric by a first multiplied coefficient to produce a first product, and sums the first product and a first added coefficient to produce the first corrected uncertainty metric; and

the second mapping function multiplies the second uncertainty metric by a second multiplied coefficient to produce a second product, and sums the second product and a second added coefficient to produce the second corrected uncertainty metric.

15. One or more non-transitory machine-readable media embodying program instructions that, when executed by one or more machines, cause the one or more machines to implement a method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

determining a first position estimate for the mobile device using a first positioning technology; and

using a second positioning technology to:

initialize a hypothesis grid, where each hypothesis in the grid has an assumed location and a weight;

for each hypothesis in the grid, recalculate the weight of that hypothesis based on a respective distance between the assumed location and the first position estimate; and

normalizing the recalculated weights such that the sum of all of the recalculated weights is equal to one;

determine a final position estimate for the mobile device using the normalized weights.

16. The one or more non-transitory machine-readable media of claim 15 , wherein the final position estimate is determined using the normalized weights by using the normalized weights as a confidence factor or measurement noise estimate in a Kalman or particle filter.

17. The one or more non-transitory machine-readable media of claim 15 , wherein for each particular hypothesis in the grid, the recalculated weight of the particular hypothesis is determined using (a) the weight of the particular hypothesis and (b) a multiplier that is determined using an exponential function of a negative value, wherein the value is determined by dividing (i) a square of the respective distance between the assumed location of the particular hypothesis and the first position estimate by (ii) a variance of the first position estimate.

18. The one or more non-transitory machine-readable media of claim 15 , wherein for each particular hypothesis in the grid, the recalculated weight of the particular hypothesis is determined using (a) the weight of the particular hypothesis and (b) a multiplier that is (i) larger than each other multiplier used to determine a respective recalculated weight of a respective hypothesis in the grid that has a respective assumed location that is further away from the first position estimate than the assumed location of the particular hypothesis, and (ii) smaller than each other multiplier used to determine a respective recalculated weight of a respective hypothesis in the grid that has a respective assumed location that is closer to the first position estimate than the assumed location of the particular hypothesis.

19. One or more non-transitory machine-readable media embodying program instructions that, when executed by one or more machines, cause the one or more machines to implement a method for estimating a position of a mobile device using information from two positioning technologies, wherein the method comprises:

for each transmitter in a transmitter network of a first positioning technology, estimating a pseudorange between an unknown location of the mobile device and a known location of that transmitter;

determining an estimated position of the unknown location of the mobile device using a second positioning technology;

determining an uncertainty metric of the estimated position;

for each transmitter in the transmitter network, determining a distance between the estimated position and the known location of that transmitter;

for each transmitter in the transmitter network, determining a pseudorange error as the difference between the estimated pseudorange for that transmitter and the determined distance for that transmitter;

determining a scale factor that is based on the uncertainty metric;

for each transmitter in the transmitter network, determining a pseudorange correction for that transmitter by scaling the determined pseudorange error for that transmitter using the scale factor; and

for each transmitter in the transmitter network, determining a corrected pseudorange for that transmitter as the difference between the estimated pseudorange for that transmitter and the pseudorange correction for that transmitter.

20. The one or more non-transitory machine-readable media of claim 19 , wherein the method comprises:

determining a final position estimate for the mobile device using the corrected pseudoranges.