Location measurement acquisition optimization with Monte Carlo simulation
The present subject matter discloses a method for estimating dilution of precision (DOP) across a service area. A Monte Carlo simulation is used to determine the DOP across a service area. Random points are selected across a service area and as well as the radio transmitters who signals are capable of being received at the random points are determined. Using the network topology of radio transmitters, a DOP is calculated for each of the random points. DOP is modeled for the service area as a function of the calculated DOP for each of the random points. The modeled DOP is used to determined the measurement accuracy required for subsequent location requests.
1. A method for estimating dilution of precision (DOP) across a service area comprising:
selecting a plurality of points across the service area;
determining a set of radio transmitters that transmit signals capable of being received in the serving area;
calculating a DOP for each point in the plurality of points based on at least a geometry of each radio transmitter in the set of radio transmitters with respect to the points; and
modeling a DOP of the service area as a function of the calculated DOP of each of the plurality of points.
2. The method of claim 1 wherein the plurality of points represent a random distribution.
3. The method of claim 1 comprising:
for every radio transmitter and point combination, determining the probability of each radio transmitters in the set of radio transmitters can be successfully measured at the plurality of points; and
calculating the DOP for each point based at least on the probability.
4. The method of claim 3 , wherein the probability is based on simulation data.
5. The method of claim 3 , wherein the probability is based on historical data.
6. A method of optimizing the number of measurements requested in a service area, comprising:
selecting a level of uncertainty;
determining a set of radio transmitters that transmit signals capable of being received in the serving area;
determining a metric across the service area based on at least the geometry of each of the radio transmitters within the set with respect to a plurality of randomly distributed points across the area; and
determining the number of measurements required at a location within the area based on at least the metric and the level of uncertainty.
7. The method of claim 6 , wherein the metric is dilution of precision (DOP).
8. The method of claim 6 , wherein the metric is a predicted uncertainty.
9. The method of claim 6 , comprising;
determining a measurement error standard deviation based at least on the metric and the level of uncertainty;
determining the number of measurements required to obtain the measurement error standard deviation based on a plurality of measurements.
10. The method of claim 9 , wherein the plurality of measurements represents simulated measurements.
11. The method of claim 9 , wherein the plurality of measurements represent historical measurements.
12. The method of claim 6 , wherein the step of determining a metric comprises:
calculating a dilution of precision (DOP) for each of the plurality of randomly distributed points based on at least a geometry of each radio transmitter in the set with respect to each of the plurality of points; and,
modeling a DOP of the area as a function of the calculated DOP for each of the plurality of points.