Wide area positioning system
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.
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 by 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;
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 method further comprises:
selecting uncorrelated noise samples to obtain information regarding a noise sub-space.
3. 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.
4. The method of claim 1 , wherein each vector of cross-correlation samples includes the peak of the cross-correlation function.
5. The method of claim 1 , wherein each vector of cross-correlation samples includes the first set of cross-correlation samples left of the peak of the cross-correlation function and the second set of cross-correlation samples right of the peak of the cross-correlation function.
6. The method of claim 1 , wherein each reference sequence is a pseudorandom sequence.
7. 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.
8. 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.
9. 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.
10. The method of claim 1 , wherein the method comprises:
calculating a Fourier Transform using the vector.
11. 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.
12. 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.
13. The method of claim 1 , wherein the method comprises:
generating a noise subspace matrix.
14. 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.
15. 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.
16. 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.
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 by 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;
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. 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 by 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;
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.
20. The one or more non-transitory computer-readable media of claim 18 , wherein the method further comprises:
selecting uncorrelated noise samples to obtain information regarding a noise sub-space.
21. 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.
22. 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.
23. The one or more non-transitory computer-readable media of claim 18 , wherein each vector of cross-correlation samples includes the first set of cross-correlation samples left of the peak of the cross-correlation function and the second set of cross-correlation samples right of the peak of the cross-correlation function.
24. The one or more non-transitory computer-readable media of claim 18 , wherein each reference sequence is a pseudorandom sequence.
25. 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.
26. The one or more non-transitory computer-readable media of claim 18 , wherein the method further 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.
27. The one or more non-transitory computer-readable media of claim 18 , wherein the method further 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.
28. The one or more non-transitory computer-readable media of claim 18 , wherein the method further comprises:
calculating a Fourier Transform using the vector.
29. The one or more non-transitory computer-readable media of claim 18 , wherein the method further 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.
30. The one or more non-transitory computer-readable media of claim 18 , wherein the method further comprises:
generating a vector of sorted singular values; and
using the vector of sorted singular values to separate signal and noise subspaces.
31. The one or more non-transitory computer-readable media of claim 18 , wherein the method further comprises:
generating a noise subspace matrix.
32. The one or more non-transitory computer-readable media of claim 18 , wherein the method further 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.
33. The one or more non-transitory computer-readable media of claim 18 , wherein the method further comprises:
determining the first position of the receiver based on a solution to a set of linearized equations using a least squares method.
34. 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.
35. 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.
36. The system of claim 19 , further comprising:
means for selecting uncorrelated noise samples to obtain information regarding a noise sub-space.
37. The system of claim 19 , 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.
38. The system of claim 19 , wherein each vector of cross-correlation samples includes the peak of the cross-correlation function.
39. The system of claim 19 , wherein each vector of cross-correlation samples includes the first set of cross-correlation samples left of the peak of the cross-correlation function and the second set of cross-correlation samples right of the peak of the cross-correlation function.
40. The system of claim 19 , wherein each reference sequence is a pseudorandom sequence.
41. The system of claim 19 , 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.
42. The system of claim 19 , further comprising:
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.
43. The system of claim 19 , further comprising:
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.
44. The system of claim 19 , further comprising:
means for calculating a Fourier Transform using the vector.
45. The system of claim 19 , further comprising:
means for generating a frequency domain estimate of a channel;
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; and
means for performing singular value decomposition on the estimated covariance matrix.
46. The system of claim 19 , further comprising:
means for generating a vector of sorted singular values; and
means for using the vector of sorted singular values to separate signal and noise subspaces.
47. The system of claim 19 , further comprising:
means for generating a noise subspace matrix.
48. The system of claim 19 , further comprising:
means for 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.
49. The system of claim 19 , further comprising:
means for determining the first position of the receiver based on a solution to a set of linearized equations using a least squares method.
50. The system of claim 19 , 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.
51. The system of claim 19 , 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.