Wide area positioning system

• US 9,591,438 B2
• Filed: 12/23/2013
• Issued: 03/07/2017
• Est. Priority Date: 09/10/2008
• Status: Active Grant

• Current Assignee: NextNav, LLC
• Original Assignee: NextNav, LLC
• Inventors: Raghupathy, Arun, Pattabiraman, Ganesh, Meiyappan, Subramanian S, Sankar, Hari
• Primary Examiner(s): LIU, HARRY K
• Application Number:
  US14/138,412
• Publication Number:
  US 20140292580A1
• Time in Patent Office: 1,170 Days
• Field of Search: 342/386
• US Class Current: 1/1
• CPC Class Codes: G01S 1/08 Systems for determining direction or position line
• CPC Class Codes: G01S 19/11 wherein the cooperating elements are pseudolites or satellite radio beacon positioning system signal repeaters
• CPC Class Codes: G01S 19/24 Acquisition or tracking or demodulation of signals transmitted by the system synchronisation aspects of direct sequence spread spectrum modulation H04B1/7073
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G01S 19/46 the supplementary measurement being of a radio-wave signal type
• CPC Class Codes: G01S 5/10 Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements , e.g. omega or decca systemsG01S5/12 takes precedence ; beacons and receivers cooperating therewith G01S1/306, G01S1/308
• CPC Class Codes: H04B 1/04 Circuits
• CPC Class Codes: H04B 1/16 Circuits
• CPC Class Codes: H04B 1/7087 Carrier synchronisation aspects
• CPC Class Codes: H04B 1/709 Correlator structure
• CPC Class Codes: H04B 2201/7073 Direct sequence modulation synchronisation
• CPC Class Codes: H04B 7/2618 using hybrid code-time division multiple access [CDMA-TDMA]
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 56/005 compensating for timing error by adjustment in the receiver
• CPC Class Codes: H04W 72/0446 Resources in time domain, e.g. slots or frames
• CPC Class Codes: H04W 72/30 Resource management for broadcast services
• CPC Class Codes: H04W 72/51 based on terminal or device properties

Abstract

Systems and methods are described for determining position of a receiver. The positioning system comprises a transmitter network including transmitters that broadcast positioning signals. The positioning system comprises a remote receiver that acquires and tracks the positioning signals and/or satellite signals. The satellite signals are signals of a satellite-based positioning system. A first mode of the remote receiver uses terminal-based positioning in which the remote receiver computes a position using the positioning signals and/or the satellite signals. The positioning system comprises a server coupled to the remote receiver. A second operating mode of the remote receiver comprises network-based positioning in which the server computes a position of the remote receiver from the positioning signals and/or satellite signals, where the remote receiver receives and transfers to the server the positioning signals and/or satellite signals.

Claims

1. A method for estimating one or more positions of a receiver, wherein the method comprises:

generating, for each of a plurality of positioning signals transmitted from a plurality of terrestrial transmitters and received by the receiver, a cross-correlation function by cross-correlating one or more signal samples extracted from that positioning signal with a reference sequence corresponding to that positioning signal;

determining a vector of cross-correlation samples from each cross-correlation function;

identifying, for each of the positioning signals, a time of arrival estimate corresponding to an earliest arriving signal path of one or more signal paths corresponding to that positioning signal using a high resolution time of arrival measurement method; and

estimating a first position of the receiver based on the time of arrival estimate.

2. The method of claim 1, wherein the time of arrival estimate identified for each of the positioning signals is identified by applying the high resolution time of arrival measurement method to the vector of cross-correlation samples corresponding to that positioning signal.

3. The method of claim 1, wherein each vector of cross-correlation samples includes the peak of the cross-correlation function.

4. The method of claim 1, wherein each vector of cross-correlation samples includes a first set of cross-correlation samples left of a peak of the cross-correlation function, and a second set of cross-correlation samples right of the peak of the cross-correlation function.

5. The method of claim 1, wherein each reference sequence is a pseudorandom sequence.

6. The method of claim 1, wherein the high resolution time of arrival measurement method is based on at least one of a MUSIC algorithm, an ESPRIT algorithm, or an Eigen-space decomposition method.

7. The method of claim 1, wherein the method comprises:

generating a reference vector from a correlation function determined by a calculated function or a measurement in a channel environment that has low noise and separable or no multipath components.

8. The method of claim 1, wherein the method comprises:

improving a signal-to-noise ratio in the vector by coherently averaging across at least one of a plurality of pseudorandom code frames and a plurality of bits.

9. The method of claim 1, wherein the method comprises:

calculating a Fourier Transform using the vector.

10. The method of claim 1, wherein the method comprises:

generating a frequency domain estimate of a channel;

generating a reduced channel estimate vector from the frequency domain estimate of the channel;

defining an estimated covariance matrix of the reduced channel estimate vector; and

performing singular value decomposition on the estimated covariance matrix.

11. The method of claim 1, wherein the method comprises:

generating a vector of sorted singular values; and

using the vector of sorted singular values to separate signal and noise subspaces.

12. The method of claim 1, wherein the method comprises:

generating a noise subspace matrix.

13. The method of claim 1, wherein the method comprises:

determining the first position of the receiver based on a non-linear objective function and a best estimate of the first position as a set of position parameters that minimize the objective function.

14. The method of claim 1, wherein the method comprises:

determining the first position of the receiver based on a solution to a set of linearized equations using a least squares method.

15. The method of claim 1, wherein the high resolution time of arrival measurement method is based on at least one of a signal space separation method, a noise space separation method, a singular value decomposition method, or a covariance estimation method.

16. The method of claim 1, wherein the method comprises:

selecting a first set of cross-correlation samples left of a peak of the cross-correlation function and a second set of cross-correlation samples right of the peak of the cross-correlation function; and

selecting uncorrelated noise samples to obtain information regarding a noise sub-space.

17. The method of claim 1, wherein the time of arrival estimate corresponding to the earliest arriving signal path is identified by:

generating a reference vector from a correlation function determined by a calculated function or a measurement in a channel environment that has low noise and separable or no multipath components;

improving a signal-to-noise ratio in the vector by coherently averaging across at least one of a plurality of pseudorandom code frames and a plurality of bits;

calculating a Fourier Transform of the vector;

generating a frequency domain estimate of a channel using the Fourier Transform of the vector and a Fourier Transform of the reference vector;

generating a reduced channel estimate vector from the frequency domain estimate of the channel;

defining an estimated covariance matrix of the reduced channel estimate vector;

performing singular value decomposition on the estimated covariance matrix;

generating a vector of sorted singular values;

using the vector of sorted singular values to separate signal and noise subspaces;

generating a noise subspace matrix; and

using the noise subspace matrix to identify the time of arrival estimate corresponding to the earliest arriving signal path.

18. One or more non-transitory computer-readable media embodying program instructions that, when executed by one or more processors, cause the one or more processors to implement a method for estimating one or more positions of a receiver, wherein the method comprises:

generating, for each of a plurality of positioning signals transmitted from a plurality of terrestrial transmitters and received by the receiver, a cross-correlation function by cross-correlating one or more signal samples extracted from that positioning signal with a reference sequence corresponding to that positioning signal;

determining a vector of cross-correlation samples from each cross-correlation function;

identifying, for each of the positioning signals, a time of arrival estimate corresponding to an earliest arriving signal path of one or more signal paths corresponding to that positioning signal using a high resolution time of arrival measurement method; and

estimating a first position of the receiver based on the time of arrival estimate.

19. The one or more non-transitory computer-readable media of claim 18, wherein the time of arrival estimate identified for each of the positioning signals is identified by applying the high resolution time of arrival measurement method to the vector of cross-correlation samples corresponding to that positioning signal.

20. The one or more non-transitory computer-readable media of claim 18, wherein each vector of cross-correlation samples includes the peak of the cross-correlation function.

21. The one or more non-transitory computer-readable media of claim 18, wherein each vector of cross-correlation samples includes a first set of cross-correlation samples left of a peak of the cross-correlation function, and a second set of cross-correlation samples right of the peak of the cross-correlation function.

22. The one or more non-transitory computer-readable media of claim 18, wherein each reference sequence is a pseudorandom sequence.

23. The one or more non-transitory computer-readable media of claim 18, wherein the high resolution time of arrival measurement method is based on at least one of a MUSIC algorithm, an ESPRIT algorithm, or an Eigen-space decomposition method.

24. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

generating a reference vector from a correlation function determined by a calculated function or a measurement in a channel environment that has low noise and separable or no multipath components.

25. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

improving a signal-to-noise ratio in the vector by coherently averaging across at least one of a plurality of pseudorandom code frames and a plurality of bits.

26. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

calculating a Fourier Transform using the vector.

27. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

generating a frequency domain estimate of a channel;

generating a reduced channel estimate vector from the frequency domain estimate of the channel;

defining an estimated covariance matrix of the reduced channel estimate vector; and

performing singular value decomposition on the estimated covariance matrix.

28. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

generating a vector of sorted singular values; and

using the vector of sorted singular values to separate signal and noise subspaces.

29. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

generating a noise subspace matrix.

30. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

determining the first position of the receiver based on a non-linear objective function and a best estimate of the first position as a set of position parameters that minimize the objective function.

31. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

determining the first position of the receiver based on a solution to a set of linearized equations using a least squares method.

32. The one or more non-transitory computer-readable media of claim 18, wherein the high resolution time of arrival measurement method is based on at least one of a signal space separation method, a noise space separation method, a singular value decomposition method, or a covariance estimation method.

33. The one or more non-transitory computer-readable media of claim 18, wherein the method comprises:

selecting a first set of cross-correlation samples left of a peak of the cross-correlation function and a second set of cross-correlation samples right of the peak of the cross-correlation function; and

selecting uncorrelated noise samples to obtain information regarding a noise sub-space.

34. The one or more non-transitory computer-readable media of claim 18, wherein the time of arrival estimate corresponding to the earliest arriving signal path is identified by:

generating a reference vector from a correlation function determined by a calculated function or a measurement in a channel environment that has low noise and separable or no multipath components;

improving a signal-to-noise ratio in the vector by coherently averaging across at least one of a plurality of pseudorandom code frames and a plurality of bits;

calculating a Fourier Transform of the vector;

generating a frequency domain estimate of a channel using the Fourier Transform of the vector and a Fourier Transform of the reference vector;

generating a reduced channel estimate vector from the frequency domain estimate of the channel;

defining an estimated covariance matrix of the reduced channel estimate vector;

performing singular value decomposition on the estimated covariance matrix;

generating a vector of sorted singular values;

using the vector of sorted singular values to separate signal and noise subspaces;

generating a noise subspace matrix; and

using the noise subspace matrix to identify the time of arrival estimate corresponding to the earliest arriving signal path.

35. A system for estimating one or more positions of a receiver, wherein the system comprises:

means for generating, for each of a plurality of positioning signals transmitted from a plurality of terrestrial transmitters and received by the receiver, a cross-correlation function by cross-correlating one or more signal samples extracted from that positioning signal with a reference sequence corresponding to that positioning signal;

means for determining a vector of cross-correlation samples from each cross-correlation function;

means for identifying, for each of the positioning signals, a time of arrival estimate corresponding to an earliest arriving signal path of one or more signal paths corresponding to that positioning signal using a high resolution time of arrival measurement method; and

means for estimating a first position of the receiver based on the time of arrival estimate.

36. The system of claims 35, wherein the system comprises:

means for selecting a first set of cross-correlation samples left of a peak of the cross-correlation function and a second set of cross-correlation samples right of the peak of the cross-correlation function; and

means for selecting uncorrelated noise samples to obtain information regarding a noise sub-space.

37. The system of claims 35, wherein the system comprises:

means for generating a reference vector from a correlation function determined by a calculated function or a measurement in a channel environment that has low noise and separable or no multipath components;

means for improving a signal-to-noise ratio in the vector by coherently averaging across at least one of a plurality of pseudorandom code frames and a plurality of bits;

means for calculating a Fourier Transform of the vector;

means for generating a frequency domain estimate of a channel using the Fourier Transform of the vector and a Fourier Transform of the reference vector;

means for generating a reduced channel estimate vector from the frequency domain estimate of the channel;

means for defining an estimated covariance matrix of the reduced channel estimate vector;

means for performing singular value decomposition on the estimated covariance matrix;

means for generating a vector of sorted singular values;

means for using the vector of sorted singular values to separate signal and noise subspaces;

means for generating a noise subspace matrix; and

means for using the noise subspace matrix to identify the time of arrival estimate corresponding to the earliest arriving signal path.