Extracting fine-tuned estimates from correlation functions evaluated at a limited number of values
First Claim
1. A method for determining one or more fine-tuned estimates of delay value associated with a received signal, the method comprising the computer-implemented steps of:
- determining a range of delay values of interest associated with the received signal;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals; and
determining the one or more fine-tuned estimates of delay value based on the fine-grained values of I and Q correlation integrals.
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Accused Products
Abstract
Techniques are provided for fine-tuning estimates of a delay value for a sampled signal. One aspect of the invention is to perform, for the sampled signal, coarse-grained calculations of the In Phase and Quadrature (I and Q) correlation integrals at a limited number of points, wherein the calculations are performed over a range of hypothesized delay values. A range of delay values of interest are then determined from the coarse-grained calculations of the I and Q correlation integrals. A subset of I and Q values based on the coarse granularity calculations of the I and Q correlation functions is used to perform a time-domain interpolation to obtain fine-grained values of the I and Q integrals in the range of the delay values of interest. Magnitude calculations are performed based on the fine-grained values of the I and Q integrals. Fine-tuned estimates of delay value are based on the magnitude calculations. Alternatively, fine-tuned estimates of delay value are based on the template-matching approach.
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Citations
41 Claims
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1. A method for determining one or more fine-tuned estimates of delay value associated with a received signal, the method comprising the computer-implemented steps of:
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determining a range of delay values of interest associated with the received signal;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals; and
determining the one or more fine-tuned estimates of delay value based on the fine-grained values of I and Q correlation integrals. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method for determining one or more fine-tuned estimates of delay value associated with a received signal, the method comprising the computer-implemented steps of:
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performing, if not already performed, a coarse-grained calculation of I and Q correlation integrals over a hypothesized range of delay values for a sampled data that is associated with the received signal;
calculating a magnitude of the coarse-grained calculations of I and Q correlation integrals over the hypothesized range of delay values; and
selecting a delay value from the hypothesized range of delay values that correspond to a highest magnitude value that corresponds to the coarse-grained calculations of I and Q correlation integrals as an initial estimate of delay value;
selecting a range of delay values in the neighborhood of the initial estimate of delay value to be a range of delay values of interest;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals;
calculating magnitude values corresponding to the fine-grained values of I and Q correlation integrals over the range of delay values of interest; and
selecting one or more delay values that corresponds to a highest magnitude value corresponding to the fine-grained values of I and Q correlation integrals as the one or more fine-tuned estimates delay value.
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15. A method for determining one or more fine-tuned estimates of delay value associated with a received signal, the method comprising the computer-implemented steps of:
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determining an initial range of delay values of interest associated with the received signal;
performing, if not already performed, a coarse-grained calculation of I and Q correlation integrals over the initial range of delay values for a sampled data that is associated with the received signal;
calculating a magnitude of the coarse-grained calculations of I and Q correlation integrals over the hypothesized range of delay values; and
selecting a delay value from the hypothesized range of delay values that correspond to a highest magnitude value that corresponds to the coarse-grained calculations of I and Q correlation integrals as an initial estimate of delay value;
selecting a range of delay values in the neighborhood of the initial estimate of delay value to be a range of delay values of interest;
generating a parametric template that represents I and Q correlation integrals associated with the received signal; and
performing a linear regression on the range of delay values of interest to produce a delay error function that is based on the range of delay values of interest; and
selecting from the range of delay values of interest one or more delay values that minimize the delay error function as the fine-tuned estimates of delay value. - View Dependent Claims (16, 17)
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18. A method for determining one or more fine-tuned estimates of carrier frequency value associated with a received signal, the method comprising the computer-implemented steps of:
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determining a range of carrier frequency values of interest associated with the received signal;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals; and
determining the one or more fine-tuned estimates of carrier frequency value based on the fine-grained values of I and Q correlation integrals. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A method for determining one or more fine-tuned estimates of carrier frequency value associated with a received signal, the method comprising the computer-implemented steps of:
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performing, if not already performed, a coarse-grained calculation of I and Q correlation integrals over a hypothesized range of carrier frequency values for a sampled data that is associated with the received signal;
calculating a magnitude of the coarse-grained calculations of I and Q correlation integrals over the hypothesized range of carrier frequency value; and
selecting a carrier frequency value from the hypothesized range of carrier frequency value that correspond to a highest magnitude value that corresponds to the coarse-grained calculations of I and Q correlation integrals as an initial estimate of carrier frequency value;
selecting a range of carrier frequency values in the neighborhood of the initial estimate of carrier frequency value to be a range of carrier frequency values of interest;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals;
calculating magnitude values corresponding to the fine-grained values of I and Q correlation integrals over the range of carrier frequency values of interest; and
selecting one or more carrier frequency value that corresponds to a highest magnitude value corresponding to the fine-grained values of I and Q correlation integrals as the one or more fine-tuned estimates carrier frequency value.
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29. A method for determining one or more fine-tuned estimates of carrier frequency value associated with a received signal, the method comprising the computer-implemented steps of:
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determining an initial range of carrier frequency values of interest associated with the received signal;
performing, if not already performed, a coarse-grained calculation of I and Q correlation integrals over the initial range of carrier frequency values for a sampled data that is associated with the received signal;
calculating a magnitude of the coarse-grained calculations of I and Q correlation integrals over the hypothesized range of carrier frequency values; and
selecting a carrier frequency value from the hypothesized range of carrier frequency values that correspond to a highest magnitude value that corresponds to the coarse-grained calculations of I and Q correlation integrals as an initial estimate of carrier frequency value;
selecting a range of carrier frequency values in the neighborhood of the initial estimate of carrier frequency value to be a range of carrier frequency values of interest;
generating a parametric template that represents I and Q correlation integrals associated with the received signal;
performing a linear regression on the range of carrier frequency values of interest to produce a carrier frequency error function that is based on the range of carrier frequency values of interest; and
selecting from the range of carrier frequency values of interest one or more carrier frequency values that minimize the carrier frequency error function as the fine-tuned estimates of carrier frequency value. - View Dependent Claims (30, 31)
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32. A method for determining one or more fine-tuned estimates of parameter values associated with a received signal, the method comprising the computer-implemented steps of:
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determining a range of parameter values of interest associated with the received signal;
interpolating fine-grained values for I and Q correlation integrals by using a subset of coarse-grained calculations of I and Q correlation integrals; and
determining the one or more fine-tuned estimates of parameter value based on the fine-grained values of I and Q correlation integrals. - View Dependent Claims (33, 34, 35, 36, 37, 38)
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39. A method for determining one or more fine-tuned estimates of parameter value associated with a received signal, the method comprising the computer-implemented steps of:
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determining an initial range of parameter values of interest associated with the received signal;
performing, if not already performed, a coarse-grained calculation of I and Q correlation integrals over the initial range of parameter values for a sampled data that is associated with the received signal;
calculating a magnitude of the coarse-grained calculations of I and Q correlation integrals over the hypothesized range of parameter values; and
selecting a parameter value from the hypothesized range of parameter values that correspond to a highest magnitude value that corresponds to the coarse-grained calculations of I and Q correlation integrals as an initial estimate of parameter value;
selecting a range of parameter values in the neighborhood of the initial estimate of parameter value to be a range of parameter values of interest;
generating a parametric template that represents I and Q correlation integrals associated with the received signal; and
performing a linear regression on the range of parameter values of interest to produce a parameter error function that is based on the range of parameter values of interest; and
selecting from the range of parameter values of interest one or more parameter values that minimize the parameter error function as the fine-tuned estimates of parameter value. - View Dependent Claims (40, 41)
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Specification