Sirf Technology, Inc.

Enuvis, Inc.

Jesse Stone

Andrew Chou

Wallace Mann

Robert G Lorenz

Benjamin Van Roy

Julien Basch

Anant Sahai

John Tsitsiklis

Stefano Casadei

Wungkum Fong

A method for detecting a positioning signal includes (a) correlating a segment of a received positioning signal with a reference signal of a selected code phase and frequency to obtain a correlation value, (b) if the correlation value is less than a predetermined minimum, assigning the correlation value to the predetermined minimum, and (c) accumulating the correlation value in a sum of correlation values obtained using other segments of the received positioning signal. In addition, the correlation value may be reduced by a predetermined value, which is preferably an expected mean value for a noise component in the segment of the received positioning signal.

Reducing memory usage in noncoherent signal processing

A method and a system for a location determination (a) acquire a first positioning signal; (b) analyze the first positioning signal to provide an estimate of a clock signal acceleration; (c) acquire additional positioning signals based on the estimate of the clock signal acceleration; and (d) perform the location determination using the first positioning signal and the additional positioning signals. The additional positioning signals may be acquired using a stacking technique. The first positioning signal may be acquired based on a signal-to-noise ratio exceeding a predetermined threshold. Clock signal acceleration may be estimated using a constant clock signal acceleration parametric model, which may be parabolic model based on a function that depends on the clock signal acceleration, a clock Doppler and an initial phase value. Alternatively, grids of various granularity may be searched clock signal acceleration space and a clock Doppler space in the vicinity of a clock Doppler value measured in the acquisition of the first positioning signal.

System and method for estimating clock acceleration and location determination

System and method to determine the location of a receiver in a multipath environment are provided. The received signal is correlated with the reference signals associated with the transmitting sources. Each correlation function is processed to derive various types of signal constraints, such as probability densities and uncertainty regions or intervals. In some embodiments, these constraints are for the code-phases and the Doppler frequencies. These signal constraints are transformed into constraints on the receiver variables and then fused together into a unified receiver constraint. A-priori constraints, such as constraints on the location of the receiver or the timestamp, may be incorporated into the unified receiver constraint. Some embodiments estimate a location based also on the estimated Doppler frequency. The constraints used by the invention are based on models of multipath effects and are geared towards mitigating these effects. In one of these models, a probability density for code-phase is obtained by convolving a gaussian distribution with an exponential distribution that describes the extra delay introduced by multipath. Another approach is based on identifying outliers in the set of code-phases. In other approaches, uncertainty region constraints and probability densities are combined. The present invention achieves faster and more sensitive signal acquisition and higher location accuracy in multipath environment, without compromising performance in other environments.

System and method to estimate the location of a receiver in a multi-path environment

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.

Extracting fine-tuned estimates from correlation functions evaluated at a limited number of values

A systematic method for acquiring positioning signals, such as global positioning system (GPS) signals, uses different signal detection algorithms at different stages of signal detection. For example, a method for detecting multiple positioning signals may include first detecting a first positioning signal using a robust but less sensitive signal detection method, such as non-coherent integration. Based on the signal parameter values that allow detection of the first positional signal, detecting a second positioning signal using a more sensitive method, such as coherent integration. In this manner, by capturing the strongest signal first using a robust method, signal detection parameter values common to positioning signals can be narrowed to allow subsequent signal acquisitions using a more sensitive&#x2014;but computationally more intensive&#x2014;method.

Using multiple detection algorithms in positioning signal processing

A method in a Global Positioning System (GPS) receiver achieves enhanced performance by scheduling searches in the Doppler search space according to a cost function. The cost function relates to both the cost of building a 3-dimensional correlation grid and the cost of searching satellite, code phase, Doppler and integration time interval spaces for values that provide a maximum in the correlation grid. In one embodiment, after the clock Doppler is determined upon acquiring one satellite, the Doppler search range associated with a cell in the grid is dominated by the receiver's own motion. The scheduler schedules searching of the Doppler search space using search ranges determined empirically by the expected receiver velocity. In one embodiment, the scheduler increases integration times before changing Doppler search ranges, which require a recalculation of the grid.

Method for optimal search scheduling in satellite acquisition

A method for providing an initial estimate for an interval of possible values for a parameter used in an acquisition of a signal maintains parameter values obtained from previous signal acquisitions and the times at which the signal acquisitions were made. The maintained values of the parameter are used to derive a candidate value for the parameter to be used in a new signal acquisition. To make the maintained values available even after a brief period during which the GPS receiver is powered down, the maintained values can be stored in a non-volatile memory. The signal acquisitions may correspond to GPS satellite signal acquisitions, and the maintained parameter values can be grouped according to whether a successful receiver location determination was accomplished.

Method for rapid location determination using parametric values obtained in a previous location determination

To determine the location of a signal receiver, sampled data received from a receiver is divided into data segments of increasing length. Current ranges for a delay value and for a modulation frequency value are calculated relative to each satellite signal source that is overhead the signal receiver. Using the data segments of increasing length, the current ranges, estimates for the delay value and for the modulation frequency value are then iteratively calculated and updated. For each signal source, I and Q correlation integrals and their magnitude values are calculated using the modulation frequency value estimate and each of a range of delay values centered around the delay value estimate. The resulting magnitude-curve is interpolated using the calculated magnitude values. The location of the receiver is calculated using the shape of the magnitude-curve to represent the I and Q correlation integrals for each signal source.

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Palo Alto, CA, United States of America

Jesse Stone