# US 11,115,078 B2 · Wide area positioning system

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 11,115,078 B2
- Document ID: US11115078B2
- Status: Granted
- Kind: B2
- Application number: 16/784,080
- Filed: 2020-02-06
- Published: 2020-07-02
- Granted: 2021-09-07
- Earliest claimed: 2008-09-10
- Assignees: NextNav, LLC
- Applicants: NextNav, LLC
- Inventors: Arun Raghupathy; Ganesh Pattabiraman; Subramanian S. Meiyappan; Hari Sankar
- Web page: https://patentgrep.com/patent/US11115078B2

## CPC

- H04B 1/7087: Carrier synchronisation aspects
- H04W 4/02: Services making use of location information
- G01S 1/08: Systems for determining direction or position line
- 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 systems}(G01S5/12 takes precedence {; beacons and receivers cooperating therewith G01S1/306, G01S1/308})
- G01S 19/11: wherein the cooperating elements are pseudolites or satellite radio beacon positioning system signal repeaters
- G01S 19/24: Acquisition or tracking {or demodulation} of signals transmitted by the system {(synchronisation aspects of direct sequence spread spectrum modulation H04B1/7073)}
- G01S 19/42: Determining position
- G01S 19/46: the supplementary measurement being of a radio-wave signal type
- H04B 1/04: Circuits
- H04B 1/16: Circuits
- H04B 1/709: Correlator structure
- H04B 7/2618: {using hybrid code-time division multiple access [CDMA-TDMA]}
- H04W 72/0446: Resources in time domain, e.g. slots or frames
- H04W 72/30: Resource management for broadcast services
- H04W 72/51: based on terminal or device properties
- H04B 2201/7073: Direct sequence modulation synchronisation
- H04W 56/005: {compensating for timing error by adjustment in the receiver}
- H04B: TRANSMISSION
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES

## 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

### Claim 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.

### Claim 2 (depends on 1)

The method of claim 1, wherein the method further comprises:
selecting uncorrelated noise samples to obtain information regarding a noise sub-space.

### Claim 3 (depends on 1)

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.

### Claim 4 (depends on 1)

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

### Claim 5 (depends on 1)

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.

### Claim 6 (depends on 1)

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

### Claim 7 (depends on 1)

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.

### Claim 8 (depends on 1)

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.

### Claim 9 (depends on 1)

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.

### Claim 10 (depends on 1)

The method of claim 1, wherein the method comprises:
calculating a Fourier Transform using the vector.

### Claim 11 (depends on 1)

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.

### Claim 12 (depends on 1)

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.

### Claim 13 (depends on 1)

The method of claim 1, wherein the method comprises:
generating a noise subspace matrix.

### Claim 14 (depends on 1)

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.

### Claim 15 (depends on 1)

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.

### Claim 16 (depends on 1)

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.

### Claim 17 (depends on 1)

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.

### Claim 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.

### Claim 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.

### Claim 20 (depends on 18)

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.

### Claim 21 (depends on 18)

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.

### Claim 22 (depends on 18)

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.

### Claim 23 (depends on 18)

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.

### Claim 24 (depends on 18)

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

### Claim 25 (depends on 18)

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.

### Claim 26 (depends on 18)

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.

### Claim 27 (depends on 18)

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.

### Claim 28 (depends on 18)

The one or more non-transitory computer-readable media of claim 18, wherein the method further comprises:
calculating a Fourier Transform using the vector.

### Claim 29 (depends on 18)

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.

### Claim 30 (depends on 18)

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.

### Claim 31 (depends on 18)

The one or more non-transitory computer-readable media of claim 18, wherein the method further comprises:
generating a noise subspace matrix.

### Claim 32 (depends on 18)

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.

### Claim 33 (depends on 18)

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.

### Claim 34 (depends on 18)

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.

### Claim 35 (depends on 18)

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.

### Claim 36 (depends on 19)

The system of claim 19, further comprising:
means for selecting uncorrelated noise samples to obtain information regarding a noise sub-space.

### Claim 37 (depends on 19)

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.

### Claim 38 (depends on 19)

The system of claim 19, wherein each vector of cross-correlation samples includes the peak of the cross-correlation function.

### Claim 39 (depends on 19)

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.

### Claim 40 (depends on 19)

The system of claim 19, wherein each reference sequence is a pseudorandom sequence.

### Claim 41 (depends on 19)

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.

### Claim 42 (depends on 19)

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.

### Claim 43 (depends on 19)

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.

### Claim 44 (depends on 19)

The system of claim 19, further comprising:
means for calculating a Fourier Transform using the vector.

### Claim 45 (depends on 19)

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.

### Claim 46 (depends on 19)

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.

### Claim 47 (depends on 19)

The system of claim 19, further comprising:
means for generating a noise subspace matrix.

### Claim 48 (depends on 19)

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.

### Claim 49 (depends on 19)

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.

### Claim 50 (depends on 19)

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.

### Claim 51 (depends on 19)

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.