System for improving average accuracy of signals from global positioning system by using a neural network to obtain signal correction values

Claim 3

An apparatus according to claim 1 further comprising: (c) an output processor for: (i) receiving the coordinate data correction values and the uncorrected, measured coordinate data, (ii) mathematically manipulating the coordinate data correction values and the uncorrected, measured coordinate data, and (iii) outputting corrected coordinate data.

Claim 4

An apparatus according to claim 2 wherein the uncorrected measured coordinate data includes latitude and longitude.

Claim 5

An apparatus according to claim 3 wherein the plurality of discrete values which are output from the data conditioner, and subsequently input into the input layer of the neural network, are a predetermined number of least significant digits of the uncorrected latitude and longitude.

Claim 6

An apparatus according to claim 4 wherein there are nine discrete values, I1-I9, and I1-I5 are the five least significant digits of the longitude measurement in arc seconds, the input I5 also including one significant digit in fractions of an arc second, and I6-I9 are the four least significant digits of the latitude measurement in arc seconds, the input I9 also including one significant digit in fractions of an arc second.

Claim 7

An apparatus according to claim 2 wherein the output processor mathematically manipulates the coordinate data correction values and the uncorrected, measured coordinate data by subtracting the coordinate data correction values from the uncorrected, measured coordinate data.

Claim 8

An apparatus according to claim 1 wherein the neural network is a three layer feedforward neural network.

Claim 9

An apparatus according to claim 1 wherein the neural network includes a hidden layer between the input layer and the output layer, and the weights include weight matrix V between the input layer and the hidden layer, and a weight matrix W between the hidden layer and the output layer.

Claim 10

An apparatus according to claim 1 wherein the uncorrected, measured coordinate data is received from an array of orbiting satellites.

Claim 11

A global positioning satellite (GPS) receiver comprising: (a) a receiver circuit for receiving uncorrected, measured coordinate data from a GPS network; (b) a data conditioner for processing the uncorrected, measured coordinate data and outputting a plurality of discrete values, the plurality of discrete values being directly related to the coordinate data; (c) an artificial neural network comprising: (i) an input layer having a plurality of inputs, each input receiving one of the plurality of discrete values, (ii) processing nodes, neurons and weights for mathematically manipulating the inputted values, and (iii) an output layer for outputting coordinate data correction values; and (d) an output processor for: (i) receiving the coordinate data correction values and the, measured uncorrected coordinate data, (ii) mathematically manipulating the coordinate data correction values and the uncorrected, measured coordinate data, and (iii) outputting corrected coordinate data.

Claim 12

A global positioning satellite (GPS) receiver comprising: (a) a receiver circuit for receiving uncorrected, measured coordinate data from a GPS network; (b) a data conditioner for processing the uncorrected, measured coordinate data and outputting a plurality of discrete values, the plurality of discrete values being directly related to the coordinate data; (c) an artificial neural network comprising: (i) an input layer having a plurality of inputs, each input receiving one of the plurality of discrete values, (ii) processing nodes, neurons and weights for mathematically manipulating the inputted values, and (iii) an output layer for outputting coordinate data correction values; and (d) an output processor for: (i) receiving the coordinate data correction values and the, measured uncorrected coordinate data, (ii) mathematically manipulating the coordinate data correction values and the uncorrected, measured coordinate data, and (iii) outputting corrected coordinate data.

Claim 13

A GPS receiver according to claim 10 wherein the uncorrected, measured coordinate data includes latitude and longitude.

Claim 14

A GPS receiver according to claim 11 wherein the plurality of discrete values which are output from the data conditioner, and subsequently input into the input layer of the neural network, are a predetermined number of least significant digits of the uncorrected latitude and longitude.

Claim 15

A GPS receiver according to claim 12 wherein there are nine discrete values, I1-I9, and I1-I5 are the five least significant digits of the longitude measurement in arc seconds, the input I5 also including one significant digit in fractions of an arc second, and I6-I9 are the four least significant digits of the latitude measurement in arc seconds, the input I9 also including one significant digit in fractions of an arc second.

Claim 16

A GPS receiver according to claim 10 wherein the neural network is a three layer feedforward neural network.

Claim 17

A GPS receiver according to claim 10 wherein the neural network includes a hidden layer between the input layer and the output layer, and the weights include weight matrix V between the input layer and the hidden layer, and a weight matrix W between the hidden layer and the output layer.

Claim 18

A GPS receiver according to claim 10 wherein the output processor mathematically manipulates the coordinate data correction values and the uncorrected, measured coordinate data by subtracting the coordinate data correction values from the uncorrected, measured coordinate data.

Claim 19

A GPS receiver according to claim 10 wherein the uncorrected, measured coordinate data is received from an array of orbiting satellites.

Claim 22

An apparatus according to claim 18 further comprising: (c) an output processor for: (i) receiving the latitude and longitude correction values and the uncorrected, measured latitude and longitude data, (ii) subtracting the latitude and longitude correction values from the uncorrected, measured latitude and longitude data, and (iii) outputting corrected latitude and longitude data.

Claim 23

An apparatus according to claim 19 wherein there are nine inputs, I1-I9, and I1-I5 are the five least significant digits of the longitude measurement in arc seconds, the input I5 also including one significant digit in fractions of an arc second, and I6-I9 are the four least significant digits of the latitude measurement in arc seconds, the input I9 also including one significant digit in fractions of an arc second.

Claim 24

An apparatus according to claim 18 wherein the neural network includes a hidden layer between the input layer and the output layer, and the weights are associated with a weight matrix V between the input layer and the hidden layer, and a weight matrix W between the hidden layer and the output layer.

Claim 27

A method according to claim 22 further comprising the step of: (f) obtaining corrected coordinate data by mathematically manipulating the coordinate data correction values and the raw, measured coordinate data.

Claim 28

A method according to claim 23 wherein step (f) includes mathematically manipulating the coordinate data correction values and the raw, measured coordinate data by subtracting the coordinate data correction values from the raw, measured coordinate data.

Claim 29

A method according to claim 22 wherein step (a), the coordinate data includes latitude and longitude.

Claim 30

A method according to claim 27 wherein step (b) includes the step of processing the raw, measured latitude and longitude data to obtain a predetermined number of least significant digits of the raw, measured latitude and longitude data, and step (c) includes the step of inputting the least significant digits into the input layer of the neural network.

Claim 31

A method according to claim 26 wherein in step (b), there are nine discrete values, I1-I9, and I1-I5 are the five least significant digits of the longitude measurement in arc seconds, the input I5 also including one significant digit in fractions of an arc second, and I6-I9 are the four least significant digits of the latitude measurement in arc seconds, the input I9 also including one significant digit in fractions of an arc second.

Claim 32

A method according to claim 22 wherein steps (c), (d) and (e) are performed by a three layer feedforward neural network.

Claim 33

A method according to claim 22 wherein steps (c), (d) and (e) are performed by a neural network which includes a hidden layer between the input layer and the output layer, and having weights including a weight matrix V between the input layer and the hidden layer, and a weight matrix W between the hidden layer and the output layer.

Claim 34

A method according to claim 22 wherein, in step (a), the GPS receiver receives the raw, measured coordinate data from an array of orbiting satellites.