CLIAMS:
1. A method of acquiring a Global Positioning System (GPS) signal, comprising:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase.

2. The method of claim 1, wherein the received GPS signal is a time domain GPS signal.

3. The method of claim 2, wherein computing the coarse estimate values of carrier frequency and pseudo random noise code phase based on the GPS signal comprises:
converting the time domain GPS signal into a frequency domain GPS signal;
computing conjugate of local signals in frequency domain; and
computing coarse estimate values of carrier frequency and pseudo random noise code phase by correlating the frequency domain GPS signal with the conjugate of local signals in the frequency domain.

4. The method of claim 3, wherein computing the fine estimate of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase comprising the steps of:
computing product of the coarse estimate value of pseudo random noise code phase with the received GPS signal;
computing product of the coarse estimate value of carrier frequency with the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal;
generating a filtered signal by applying a filter on the computed product of the coarse estimate value of carrier frequency and the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal, wherein the filtered signal is having a first sampling frequency;
generating a plurality of samples having a second sampling frequency by decimating and interpolating the filtered signal; and
computing a fine estimate value of carrier frequency by performing frequency analysis on the plurality of samples.

5. A method comprising:
computing estimate of carrier frequency and pseudo random noise code phase of a GPS signal received from a GPS satellite;
tracking variations in carrier frequency and pseudo random noise code phase based on the estimate of carrier frequency and pseudo random noise code phase; and
determining velocity and position based on the tracked variations in carrier frequency and pseudo random noise code phase; characterized in that, computing the estimate of carrier frequency and pseudo random noise code phase of the GPS signal comprises:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase.

6. The method of claim 5, wherein the received GPS signal is a time domain GPS signal.

7. The method of claim 6, wherein computing the coarse estimate values of carrier frequency and pseudo random noise code phase based on the GPS signal comprises:
converting the time domain GPS signal into a frequency domain GPS signal;
computing conjugate of local signals in frequency domain; and
computing coarse estimate values of carrier frequency and pseudo random noise code phase by correlating the frequency domain GPS signal with the conjugate of local signals in the frequency domain.

8. The method of claim 5, wherein computing the fine estimate of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase comprising the steps of:
computing product of the coarse estimate value of pseudo random noise code phase with the received GPS signal;
computing product of the coarse estimate value of carrier frequency with the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal;
generating a filtered signal by applying a filter on the computed product of the coarse estimate value of carrier frequency and the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal, wherein the filtered signal is having a first sampling frequency;
generating a plurality of samples having a second sampling frequency by decimating and interpolating the filtered signal; and
computing a fine estimate value of carrier frequency by performing frequency analysis on the plurality of samples.

9. A method of computing a fine estimate of carrier frequency of carrier frequency and pseudo random noise code phase comprising the steps of:
generating a filtered signal by processing coarse estimate value of carrier frequency and pseudo random noise code phase and the received GPS signal, wherein the filtered signal is having a first sampling frequency;
generating a plurality of samples having a second sampling frequency by decimating and interpolating the filtered signal; and
computing a fine estimate value of carrier frequency by performing frequency analysis on the plurality of samples.

10. The method as claimed in claims 9, wherein generating the filtered signal by processing coarse estimate value of carrier frequency and pseudo random noise code phase and the received GPS signal comprising steps of:
computing product of coarse estimate value of pseudo random noise code phase with the received GPS signal;
computing product of the coarse estimate value of carrier frequency with the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal; and
generating the filtered signal by applying a filter on the computed product of the coarse estimate value of carrier frequency and the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal.

11. An apparatus comprising:
a processor configured for:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase.

12. The apparatus of claim 11, wherein in computing the coarse estimate values of carrier frequency and pseudo random noise code phase based on the GPS signal, the processor comprises:
converting the time domain GPS signal into a frequency domain GPS signal;
computing conjugate of local signals in frequency domain; and
computing coarse estimate values of carrier frequency and pseudo random noise code phase by correlating the frequency domain GPS signal with the conjugate of local signals in the frequency domain.

13. The apparatus of claim 12, wherein in computing the fine estimate of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase, the processor is configured for:
computing product of the coarse estimate value of pseudo random noise code phase with the received GPS signal;
computing product of the coarse estimate value of carrier frequency with the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal;
generating a filtered signal by applying a filter on the computed product of the coarse estimate value of carrier frequency and the computed product of the coarse estimate value of pseudo random noise code phase and the received GPS signal, wherein the filtered signal is having a first sampling frequency;
generating a plurality of samples having a second sampling frequency by decimating and interpolating the filtered signal; and
computing a fine estimate value of carrier frequency by performing frequency analysis on the plurality of samples.

14. A device comprising:
a GPS antenna configured for receiving a GPS signal from a GPS satellite; and
a GPS receiver configured for:
computing estimate of carrier frequency and pseudo random noise code phase of a GPS signal received from a GPS satellite;
tracking variations in carrier frequency and pseudo random noise code phase based on the computed estimate of carrier frequency and pseudo random noise code phase of the GPS signal; and
determining velocity and position based on the tracked variations in carrier frequency and pseudo random noise code phase, wherein in computing the estimate of carrier frequency and pseudo random noise code phase, the GPS receiver is configured for:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase.

15. A global positioning system (GPS) receiver comprising:
an acquisition module configured for:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase;
a tracking module configured for tracking variations in carrier frequency and pseudo random noise code phase based on the computed fine estimate of carrier frequency of GPS signal and the computed coarse estimate value of pseudo random noise code phase; and
a position and velocity determination module configured for determining velocity and position based on the tracked variations in carrier frequency and pseudo random noise code phase.

16. A non-transitory computer-readable storage medium having stored instructions therein, that when executed by a processor, cause the processor to perform method comprising:
computing coarse estimate values of carrier frequency and pseudo random noise code phase based on a GPS signal received from a GPS satellite; and
computing a fine estimate value of carrier frequency based on the coarse estimate of the carrier frequency and the pseudo random noise code phase. ,TagSPECI:FIELD OF THE INVENTION

The present invention generally relates a field of Global Positioning Systems, and more particularly relates to a low latency GPS receiver.

BACKGROUND OF THE INVENTION

A Global Positioning System (GPS) is a space-based satellite navigation system that provides location, time information and velocity of an object on earth with a GPS receiver. The GPS uses between 24 and 32 Medium Earth Orbit satellites that transmit precise microwave signals. The GPS receiver is capable of solving the navigation equations in order to determine the location, velocity and time information, by processing signals broadcasted by GPS satellites. Software-defined radio (SDR) is a radio communication technology that is implemented in a GPS receiver based on software defined wireless communication protocols instead of hardwired implementations.

A typical GPS receiver consists of an antenna, a front end block and a processing block. The antenna receives global positioning system signal from a global positioning satellite and the front end of the GPS receiver, which typically down-converts, filters, amplifies and digitizes the incoming signals. The processing block includes an acquisition unit, tracking unit and a navigation unit. The acquisition unit estimates the carrier frequency and pseudo random noise code phase of the received GPS signal. The tracking unit identifies fine variations in carrier frequency and pseudo random noise code phase based on the computed fine estimate of carrier frequency of GPS signal. The output of the tracking unit is used by the navigation unit in order to determine the position and velocity of the receiver.

Typically, the acquisition unit computes coarse estimate of carrier frequency and pseudo random noise code phase and fine estimate of carrier frequency based on the coarse estimate of the carrier frequency. Since the acquisition unit does not make use of coarse estimate of pseudo random noise code phase, computation of fine estimate of the carrier frequency requires the batches of incoming GPS data to be stored and processed. This may lead to higher processing power due to complex data processing, thereby affecting overall performance of GPS receivers.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS

Figure 1 illustrates a block diagram of an exemplary Global Positioning System (GPS) receiver, according to one embodiment.

Figure 2 illustrates a block diagram of an exemplary Assisted GPS (AGPS) receiver connected to an AGPS server, according to another embodiment.

Figure 3 illustrates a detailed block diagram of a GPS receiver such as those shown in Figure 1, according to one embodiment.

Figure 4 illustrates a detailed block diagram of an acquisition module of the baseband processor, according to one embodiment.

Figure 5 is a process flowchart illustrating an exemplary method of computing position and velocity of the GPS receiver, according to one embodiment.

Figure 6 is a process flowchart illustrating an exemplary method of acquiring a GPS signal for computing the position and velocity of the GPS receiver, according to one embodiment.

Figure 7 is a process flowchart illustrating an exemplary method of performing coarse estimation of the GPS signal, according to one embodiment.

Figure 8 is a process flowchart illustrating an exemplary method of performing fine estimation of a GPS signal, according to one embodiment.

DETAILED DESCRIPTION OF THE INVENTION

A low latency global positioning system (GPS) receiver is disclosed. In the following detailed description of the embodiments of the invention, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims.

Figure 1 illustrates a block diagram of an exemplary GPS receiver 100, according to one embodiment. The GPS receiver 100 may be embedded in an electronic device 101 such as a GPS navigator, a smart phone, a tablet, a phablet, and other GPS based devices. In some embodiments, the GPS receiver 100 may be a Software Defined Radio (SDR) receiver. In these embodiments, the GPS receiver 100 includes a GPS antenna 102, a baseband processor 106 and an embedded processor 108. In other embodiments, the GPS receiver 100 includes a GPS antenna 102 and a single processor capable of performing functionalities of the baseband processor 106 and the embedded processor 108.

In an exemplary operation, the GPS antenna 102 receives a GPS signal 104 from a GPS satellite. The baseband processor 106 processes the received GPS signal 104 and feeds the processed GPS signal into the embedded processor 108. According to the present invention, the baseband processor 106 computes coarse and fine estimate values of carrier frequency and pseudo random noise code phase F ^_coarse (t) of the GPS signal 104. The baseband processor 106 tracks fine variations in the carrier frequency and pseudo random noise code phase of the GPS signal 104 based on the fine estimate of the carrier frequency C ^_fine (t) and pseudo random noise code phase of the GPS signal 104. Accordingly, the embedded processor 108 determines position and velocity of the electronic device 101 embedding the GPS receiver 104.

Figure 2 illustrates a block diagram of an exemplary AGPS receiver 200 connected to an AGPS server 210, according to another embodiment. The AGPS server 210 provides assistance information such as satellite ephemeris, GPS time, Doppler frequency, visible satellites and approximate code phase to the baseband processor 106 of the AGPS receiver 200.

Generally, in deep urban areas, GPS signals are frequently masked and attenuated by buildings. This may result in condition of loss-of-lock and determination of position and velocity become impossible. In such conditions, the AGPS server 210 sends assistance information such as ephemeris, satellite time, satellite visibility, signal to noise ratio etc. to the AGPS receiver 200 so that the AGPS receiver 200 performs faster re-acquisition of GPS signals compared to the conventional GPS receivers. The AGPS receiver 200 helps in reducing latency in acquiring the GPS signal 104 from 12 to 30 seconds to about 8 to 25 seconds.

Figure 3 illustrates a detailed block diagram of the AGPS receiver 102, according to one embodiment. The baseband processor 106 includes an acquisition module 302, and a tracking module 306, and the embedded processor 108 includes a position and velocity determination module 310.

The acquisition module 302 estimates value of carrier frequency and pseudo random noise code phase of the received GPS signal 104. The acquisition module 302 includes a coarse acquisition module 304 and a fine acquisition module 306.

The coarse acquisition module 304 computes coarse estimate values of carrier frequency and pseudo random noise code phase F ^_coarse (t) of the received GPS signal 104 in frequency domain. The fine acquisition module 306 computes fine estimate of the carrier frequency of the received GPS signal 104 based on the computed coarse estimate values of the carrier frequency and the pseudo random noise code phase of the received GPS signal 104.

The tracking module 308 tracks fine variations in the carrier frequency and the pseudo random noise code phase of the GPS signal 104 based on the computed fine estimate value of the carrier frequency of the received GPS signal 104 and the computed coarse estimate value of the pseudo random noise code phase. In some embodiments, the tracking loop 308 includes a Costas Phase Locked Loop (CPLL) to track variation in the carrier frequency of the GPS signal 104 and a Delay Locked Loop (DLL) to track variation in the pseudo random noise code phase. In an exemplary embodiment, the estimated values of carrier frequency C ^_fine (t) and the pseudo random noise code phase F ^_coarse (t) are fine-tuned by the CPLL and the DLL iteratively until the error in the carrier frequency is less than 2Hz and error in the pseudo random noise code phase to less than 1/1000 of a chip.

The position and velocity determination module 310 determines position and velocity of the GPS receiver 100 based on the data received from the tracking module 308. In one embodiment, the data received from the tracking module 308 includes pseudo range and delta pseudo range. In this embodiment, the position and velocity of the GPS receiver 100 is determined based on the values of pseudo range and delta pseudo range, respectively. One skilled in the art will understand that the position and the velocity of the electronic device 101 can be computed using a least square algorithm or a Kalman filter algorithm.

Figure 4 illustrates a detailed block diagram of the acquisition module 302 of the baseband processor 106 as shown in Figure 3. As illustrated, the coarse acquisition module 304 includes a Fast Fourier Transform (FFT) 402, a local signal generator 403, a coarse estimation module 404, and an Inverse Fast Fourier Transform (IFFT) 405. The fine acquisition module 306 includes a first multiplier 406, a second multiplier 408, a filter 410, a decimator 412 and a FFT 414.

The GPS antenna 102 feeds GPS signal 104 in time domain received from a GPS satellite to the acquisition module 302. The received GPS signal 104 may be represented as follows:

The FFT 402 converts a GPS signal 104 received from the GPS antenna 102 from time domain to frequency domain. The GPS signal 104 in frequency domain may be represented as follows:

The local signal generator 403 generates a local signal in time domain. The local signal in time domain is formed of pseudo random noise code phase and carrier frequency. Generally, the carrier frequency of the local signal is initially set to 7 KHz and multiplied with 1023 pseudo random noise code phase incrementally. The local signal generated by the local signal generator 403 in time domain may be represented as follows:

The local signal generator 403 converts the local signal from time domain to frequency domain and computes a conjugate of the generated local signal and feeds the conjugate of the local signal to the coarse estimation module 404. The coarse estimation module 404 correlates the received GPS signal 104 in frequency domain with the conjugate of the local signal in frequency domain. The coarse estimate values of carrier frequency and pseudo random noise code F ^_coarse (t) in frequency domain is computed based on the correlation value of received GPS signal 104 in frequency domain with the conjugate of the local signal in frequency domain.

The GPS signal 104 is declared to have been acquired, once the correlation value of the received GPS signal 104 in frequency domain with the conjugate of the local signal in frequency domain exceeds a pre-defined threshold value. If the correlated output does not exceed the pre-defined threshold value, the carrier frequency of the local signal is incremented by 1 KHz from the previously set value of 7KHz until the output of the coarse estimate module 404 exceeds the pre-defined threshold value. The pre-defined threshold value is a statistical parameter threshold as several parameters influence the GPS signal variations which are random in nature. For instance, atmospheric errors such as ionsopheric and tropospheric errors, satellite and receiver clock errors, receiver noises, interferences and intentional and unintentional jamming, etc. randomly affect the signal. The significant parameters associated with the determination of the pre-defined threshold are Probability of Detection (PD) and Probability of False Alarm (PFA). Generally, for a GPS receiver, the PD is set to 85% and PFA is set to 1e-4.

The IFFT 405 converts the coarse estimate values of the carrier frequency and the pseudo random noise code phase from frequency domain to time domain and feeds the coarse estimate values of the carrier frequency and the pseudo random noise code phase in the time domain to the fine acquisition module 306.

The first multiplier 406 multiplies the coarse estimate value of pseudo random noise code phase F ^_coarse (t) with the received GPS signal 104 to obtain (FIF + FD). The second multiplier 408 multiplies the coarse estimate value of the carrier frequency ( = (FIF +F ^_D1) with the output (FIF + FD) of the first multiplier 406 to obtain (Fmix). The Fmix is represented as:

The filter 410 generates a filtered signal (Fdiff) having a first sampling frequency by applying a filter on the output (Fmix) of the second multiplier 408. Since, the value (FD – FD1) is less than 1 KHz, the filter 410 filters higher order harmonics from Fmix. Thus, the frequency of the filtered signal (Fdiff) is equivalent to FD - FD1. It can be that the first sampling frequency (fs) is same as the sampling frequency of the received GPS signal 104.

The sampling frequency of the filtered signal (Fdiff) is reduced to a second sampling frequency to minimize computations in the FFT 414. The decimator 412 generates a plurality of samples having a second sampling frequency by decimating the filtered signal (Fdiff) having the first sampling frequency. In some embodiments, the samples at the second sampling frequency are interpolated using an interpolator to meet the minimum number of samples required to be input to the FFT 414. Thus, the combination of the decimator 412 and the interpolator (not shown) provides optimized number of samples to the FFT 414. The FFT 414 performs frequency analysis of the plurality of samples and computes a fine estimate value of carrier frequency based on the frequency analysis. An exemplary method of estimating the carrier frequency and pseudo random code phase in accordance with the embodiment of present invention is illustrated in Figure 6.

In an exemplary operation, consider that resolution in carrier frequency obtained by the acquisition module 302 is represented as fs/N, where fs is sampling frequency of the received GPS signal 104 and N is size of the FFT 402 used in the coarse acquisition module 304. For example, let carrier frequency of the received GPS signal 104 be 21.254MHz , and sampling frequency of the GPS signal 104 be 5MHz. Further, the size of the FFT 402 used in the coarse acquisition module 304 is 5000 points as total number of sampled required for 1ms integration period (i.e., one complete pseudo random noise code sequence) is 5000 samples. In such case, the coarse estimate value of the carrier frequency computed by the coarse acquisition module 304 is 1 KHz (i.e., fs/N = 5Mhz/5000) and the coarse estimate value of pseudo random noise code is 0.5 chips. One skilled in the art may understand that the coarse estimate of the carrier frequency equal to 1MHz may not be sufficient for the tracking loop 308 to demodulate the GPS signal 104. Thus, a fine estimation of the carrier frequency needs to be computed and provided to the tracking loop 308 for demodulation of the GPS signal 104.

According to the present invention, the coarse estimate values of the carrier frequency (i.e., = 1KHz) and pseudo random noise code phase (i.e.,
F ^_coarse (t)= 0.5 chips) are fed in to the fine acquisition module 306. The fine acquisition module 306 multiplies F ^_coarse (t) with the received GPS signal 104 having frequency FIF. Further, the fine acquisition module 306 multiplies the product (FIF + FD) with the coarse estimate value of the carrier frequency (F ^_coarse (t)) to obtain Fmix. The fine acquisition module 306 generates a filtered signal (Fdiff) by applying a low pass filter on the Fmix. It can be noted that the Fdiff is having same sampling frequency (equal to 5MHz) as the frequency of the received GPS signal (FIF).

As the frequency of the filtered signal (Fdiff) is less than 1KHz, then the fine acquisition module 306 decimates the filtered signal (Fdiff) by a decimating factor (M) to reduce computations at the FFT 414. For example, consider that the decimating factor (M) is equal to 100. In such case, the fine acquisition module 306 decimates the filter signal sampled at the sampling frequency equal to 5MHz to the sampling frequency of 50 KHz (i.e., Fs = 5MHz/100 = 50MHz). Consequently, the value of Fdiff is reduced to 50. Further, the fine acquisition module 306 interpolates 50 samples to obtain 5000 samples. The fine acquisition module 306 computes fine estimate value of the carrier frequency based in the interpolated samples. For example, the fine acquisition module 306 computes fine estimate value of the carrier frequency equal to 10Hz (i.e., 50KHz/5000) since the FFT 414 is of size equal to 5000 points and the downsampled frequency is equal to 50KHz. It can be noted that, since the fine acquisition module 306 does not buffer the received GPS signal 104, the latency in acquiring the GPS signal is equal to 1msec.

The obtained fine estimate value of the carrier frequency and the coarse estimate value of the pseudo random noise code phase are fed to the tracking loop 308. The DLL of the tracking loop 308 provides pseudo-range (geometric distance + errors) measurements for calculating position of the GPS receiver 100. The pseudo-range measurements are obtained by measuring time difference between the received and the transmitted GPS signal. The CPLL of the tracking loop 308 also provides delta pseudo-range (change in distance) measurements for calculating velocity of the GPS receiver 100. The position/velocity parameters are then combined with the pseudo-ranges and delta-pseudo ranges by a position and velocity determination module 310 using least-square or Kalman filter algorithm to estimate position and velocity of the GPS receiver 100.

Figure 5 is a process flowchart 500 illustrating an exemplary method of computing position and velocity of the GPS receiver 100, according to one embodiment. At step 502, coarse estimate values of the carrier frequency and the pseudo random noise code phase of a GPS signal 104 and a fine estimate value of the carrier frequency are computed. According to the present invention, the fine estimate value of the carrier frequency is computed based on the coarse estimate values of the carrier frequency F ^_coarse (t) and the pseudo random noise code phase F ^_coarse (t), and the received GPS signal 104. At step 504, fine variations in the carrier frequency and the pseudo random noise code phase are tracked based on the computed fine estimate of carrier frequency of the GPS signal 104 and the coarse estimate value of the pseudo random noise code phase. At step 506, position and velocity of the GPS receiver 100 is determined based on the fine variations in the carrier frequency and the pseudo random noise code phase.

Figure 6 is a process flowchart 600 illustrating an exemplary method of acquiring a GPS signal 104 by the acquisition module 302, according to one embodiment. At step 602, coarse estimate values of carrier frequency and pseudo random noise code phase are computed based on the GPS signal 104 received from a GPS satellite. The detailed method steps involved in computing coarse estimate values of carrier frequency and pseudo random noise code phase is illustrated in Figure 7.

At step 604, a fine estimate value of carrier frequency is computed based on the coarse estimate value of the carrier frequency and the pseudo random noise code phase. A detailed method steps involved in computing the fine estimate value of the carrier frequency is illustrated in Figure 8.

Figure 7 is a process flowchart 700 illustrating an exemplary method of performing a coarse estimation of a GPS signal 104, according to one embodiment. At step 702, a GPS signal 104 received from a GPS satellite in time domain is converted into frequency domain. At step 704, a local signal in time domain is converted into frequency domain and conjugate of the local signal in frequency domain is computed.

At step 706, coarse estimate values of carrier frequency and pseudo random noise code phase is computed by correlating the frequency domain GPS signal with the conjugate of the local signal in frequency domain. For example, the coarse estimate values are computed using the following equation:

Figure 8 is a process flowchart 800 illustrating an exemplary method of performing fine estimation of the GPS signal 104, according to one embodiment. At step 802, product (FIF + FD) of the coarse estimate value of pseudo random noise code phase and the received GPS signal 104 (yIF (t)) as shown in the following equation:

’

where, FIF is the incoming frequency of the received GPS signal 104, and FD is doppler frequency on the incoming frequency.

At step 804, product (Fmix) of the coarse estimate value of the carrier frequency F ^_coarse (t) with the product (FIF + FD) of the coarse estimate value of the pseudo random noise code phase and the received GPS signal 104 is computed.

At step 806, the computed product (Fmix) is filtered using a low pass filter to obtain a filtered signal (Fdiff). In one exemplary implementation, the product (Fmix) obtained at step 804 is filtered using an elliptic IIR filter (of order 3 or less). It can be noted that the filtered signal (Fdiff) is having a first sampling frequency same as sampling frequency of the GPS signal 104.

At step 808, a plurality of samples having a second sampling frequency is obtained by decimating and interpolating the filtered signal (Fdiff) having the first sampling frequency. At step 810, a frequency analysis of the plurality of samples is performed to obtain a fine estimate of the carrier frequency.

In accordance with the various embodiments described in systems and methods disclosed in Figures 1 to 8, the present invention assist in significant reduction of size of batches of incoming GPS signal by using coarse estimate value of pseudo random noise code phase to compute fine estimate of carrier frequency, thereby leading to significant reduction in latency (e.g., to about 1msec) and processing power of the electronic device 101. Accordingly, the present invention significantly reduces battery power consumption of the electronic device 101 employing the GPS receiver 100 or the AGPS 200. Further, the present invention enables the GPS receiver 100 or AGPS 200 in rapid acquisition of GPS signals in foliage and deep urban areas.

The present embodiments have been described with reference to specific example embodiments; it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the various embodiments. Furthermore, the various devices, modules, and the like described herein may be enabled and operated using hardware circuitry, for example, complementary metal oxide semiconductor based logic circuitry, firmware, software and/or any combination of hardware, firmware, and/or software embodied in a machine readable medium. For example, the various electrical structure and methods may be embodied using transistors, logic gates, and electrical circuits, such as application specific integrated circuit.