System for geo-location

• US 8,922,426 B1
• Filed: 02/26/2010
• Issued: 12/30/2014
• Est. Priority Date: 02/26/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Smith, Russell, Clement, Romain
• Primary Examiner(s): Issing, Gregory C
• Application Number:
  US12/713,690
• Time in Patent Office: 1,768 Days
• Field of Search: 342/357.23, 342/357.25, 342/357.58, 701/470, 701/480
• US Class Current: 342/357.23
• CPC Class Codes: G01S 19/20 Integrity monitoring, fault detection or fault isolation of space segment
• CPC Class Codes: G01S 19/393 Trajectory determination or predictive tracking, e.g. Kalman filtering
• CPC Class Codes: G01S 19/396 Determining accuracy or reliability of position or pseudorange measurements
• CPC Class Codes: G01S 19/40 Correcting position, velocity or attitude
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled

Abstract

A method, computer program product, and system are provided for position estimation in a geo-location system. For example, the method can include receiving a plurality of position measurements from a respective plurality of satellites in a global navigation satellite system. From the plurality of position measurements, a position measurement with a maximum pseudo-range residual value can be selected. A position uncertainty estimate can be determined based on the position measurement with the maximum pseudo-range residual value. Further, a position estimation algorithm can receive the position uncertainty estimate as an input, thereby improving position estimation of the geo-location system.

Claims

1. A method for improving position estimation in a geo-location system, comprising:

receiving, by a receiver module, a plurality of time signals from a respective plurality of satellites in a global navigation satellite system,

generating, by one or more processors, a position estimate for the receiver module using the plurality of time signals;

determining, by the one or more processors, a respective pseudo-range residual value for each of the plurality of satellites to generate a plurality of pseudo-range residual values, wherein each pseudo-range residual value represents a respective error associated with (i) the position estimate for the receiver and (ii) a time signal received from the corresponding one of the plurality of satellites, wherein the time signal is one of the plurality of time signals;

selecting, by the one or more processors from the plurality of satellites, a satellite corresponding to a maximum pseudo-range residual value in the plurality of pseudo-range residual values;

using the maximum pseudo-range residual value to determine, by the one or more processors, a position uncertainty estimate; and

providing, by the one or more processors, the position uncertainty estimate as an input to a position estimation algorithm.

2. The method of claim 1, wherein receiving the plurality of time signals comprises receiving the plurality of time signals with a plurality of single-frequency band global navigation satellite system receivers.

3. The method of claim 1, wherein selecting the satellite corresponding to the maximum pseudo-range residual value comprises:

scaling each of the plurality of pseudo-range residual values based on an elevation and a signal strength of the corresponding one of the plurality of satellites to generate a plurality of scaled pseudo-range residual values; and

selecting a scaled pseudo-range residual value with a maximum value from the plurality of scaled pseudo-range residual values.

4. The method of claim 1, wherein providing the position uncertainty estimate comprises over-estimating a geographic position measurement error.

5. The method of claim 4, wherein over-estimating the geographic position measurement error comprises converging on a solution for geographic position measurement based on a Kalman filter calculation.

6. The method of claim 5, wherein converging on the solution based on the Kalman filter comprises using a state vector based on velocity information relative to an inertial measurement unit.

7. A system for geo-location, comprising:

a plurality of global navigation satellite system receivers configured to receive a plurality of time signals from a respective plurality of global navigation satellites; and

a processing unit configured to;

generate a position estimate for the system using the plurality of time signals,

determine a respective pseudo-range residual value for each of the plurality of global navigation satellites to generate a plurality of pseudo-range residual values, wherein each pseudo-range residual value represents a respective error associated with (i) the position estimate for the system and (ii) a time signal received from the corresponding one of the plurality of global navigation satellites, wherein the time signal is one of the plurality of time signals,

select, from the plurality of satellites, a satellite corresponding to a maximum pseudo-range residual value in the plurality of pseudo-range residual values;

use the maximum pseudo-range residual value to determine a position uncertainty estimate, and

provide the position uncertainty estimate as an input to a position estimation algorithm.

8. The system of claim 7, further comprising:

an inertial measurement unit configured to determine a positional orientation of the geo-location system;

a rangefinder module configured to determine a distance of an object from the geo-location system;

an encoder configured to determine velocity of the geo-location system;

a power module configured to supply power to the rangefinder module; and

a controller-area network (CAN) bus configured to enable the processing unit to communication with a vehicle.

9. The system of claim 7, wherein the processing unit is configured to:

scale each of the plurality of pseudo-range residual values based on an elevation and a signal strength of the corresponding one of the plurality of satellites to generate a plurality of scaled pseudo-range residual values, and

select a scaled pseudo-range residual value with a maximum value from the plurality of scaled pseudo-range residual values.