CLOUD-OFFLOADED POSITION CALCULATION WITH ON-DEVICE ACQUISITION

• US 20180364361A1
• Filed: 06/15/2017
• Published: 12/20/2018
• Est. Priority Date: 06/15/2017
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Liu, Jie, Priyantha, Nissanka Arachchige Bodhi, Joppa, Lucas N, Xu, Qiang
• Granted Patent: US 10,545,244 B2
• Time in Patent Office: Days
• CPC Class Codes: G01S 19/09 providing processing capability normally carried out by the receiver
• CPC Class Codes: G01S 19/24 Acquisition or tracking or demodulation of signals transmitted by the system synchronisation aspects of direct sequence spread spectrum modulation H04B1/7073
• CPC Class Codes: G01S 19/29 carrier including Doppler, related G01S19/246 takes precedence
• CPC Class Codes: G01S 19/30 code related G01S19/246 takes precedence
• CPC Class Codes: G01S 19/34 Power consumption
• CPC Class Codes: G01S 19/37 Hardware or software details of the signal processing chain

Abstract

Methods, systems, and computer programs are presented for cloud-offloaded position calculation with on-device acquisition. One method includes operations for collecting raw global positioning system (GPS) signals for a set of positions, and storing in memory the raw GPS signals. The method further includes processing the raw GPS signals in batch mode at the computing device to obtain acquisition data for the positions, where the processing includes identifying tasks for parallel processing by a graphics processing unit (GPU), performing, by the GPU, the tasks in parallel by assigning each of the tasks to a core processor within the GPU, and combining results from performing the tasks to obtain the acquisition data. Additionally, the method includes an operation for transmitting the acquisition data to a server for calculating locations for the set positions at the server, the server storing the locations and making the locations available for location-tracking applications.

Claims

1. A method comprising:

collecting, by one or more processors of a computing device, raw global positioning system (GPS) signals for a plurality of positions;

storing in memory, by the computing device, the raw GPS signals for the plurality of positions;

processing the raw GPS signals in batch mode at the computing device to obtain acquisition data for the plurality of positions, the processing further comprising;

identifying, by the one or more processors, a plurality of tasks for parallel processing by a graphics processing unit (GPU);

performing, by the GPU, the plurality of tasks in parallel by assigning each of the tasks to a core processor within the GPU, and

combining, by the one or more processors, results from performing the plurality of tasks to obtain the acquisition data; and

transmitting, by the one or more processors, the acquisition data to a server for calculating locations for the plurality of positions at the server, the server storing the locations and making the locations available for location-tracking applications.

2. The method as recited in claim 1, further comprising:

waking up the GPU before processing the plurality of tasks; and

putting the GPU to sleep after obtaining the acquisition data.

3. The method as recited in claim 1, wherein processing the raw GPS signals comprises a parallel code search.

4. The method as recited in claim 3, wherein the parallel code search comprises:

mixing an incoming signal to baseband and an in-phase signal, where quadrature components are used as real and imaginary inputs when calculating a DFT by performing a fast Fourier transform (FFT) to obtain a first result; and

multiplying the first result by a complex conjugate of DFT of a PRN code generated by a PRN code generator to obtain a second result.

5. The method as recited in claim 4, wherein the parallel code search further comprises:

performing an inverse fast Fourier transform (IFFT) of the second result to obtain a third result; and

obtaining a square of the third result to obtain the acquisition data.

6. The method as recited in claim 1, wherein the transmitted acquisition data comprises timestamps, Doppler, and phase shift information.

7. The method as recited in claim 1, wherein the raw GPS signals include 2 ms of GPS baseband signal.

8. The method as recited in claim 1, wherein processing the raw GPS signals comprises a serial search acquisition.

9. The method as recited in claim 8, wherein the serial search acquisition comprises:

multiplying an incoming signal by a locally generated PRN sequence to obtain a first result;

multiplying the first result by a locally generated carrier signal to obtain an in-phase signal I; and

multiplying the first result by a 90°

phase-shifted version of a locally generated carrier to generate a quadrature signal Q.

10. The method as recited in claim 9, wherein the serial search acquisition further comprises:

integrating the I and Q signals over 1 ms; and

squaring the integrated I and Q signals to obtain the acquisition data.

11. A system comprising:

a memory comprising instructions;

a graphics processing unit (GPU); and

one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the one or more computer processors to perform operations comprising;

collecting raw GPS signals for a plurality of positions;

storing in the memory the raw GPS signals for the plurality of positions;

processing the raw GPS signals in batch mode to obtain acquisition data for the plurality of positions, the processing further comprising;

identifying a plurality of tasks for parallel processing by the GPU, the GPU performing the plurality of tasks in parallel by assigning each of the tasks to a core processor within the GPU; and

combining results from performing the plurality of tasks to obtain the acquisition data; and

transmitting the acquisition data to a server for calculating locations for the plurality of positions at the server, the server storing the locations and making the locations available for location-tracking applications.

12. The system as recited in claim 11, wherein the instructions further cause the one or more computer processors to perform operations comprising:

waking up the GPU before processing the plurality of tasks; and

putting the GPU to sleep after obtaining the acquisition data.

13. The system as recited in claim 11, wherein processing the raw GPS signals comprises a parallel code search, wherein the parallel code search comprises:

mixing an incoming signal to baseband and an in-phase signal, where quadrature components are used as real and imaginary inputs when calculating a DFT by performing a fast Fourier transform (FFT) to obtain a first result; and

multiplying the first result by a complex conjugate of DFT of a PRN code generated by a PRN code generator to obtain a second result.

14. The system as recited in claim 13, wherein the parallel code search further comprises:

performing an inverse fast Fourier transform (IFFT) of the second result to obtain a third result; and

obtaining a square of the third result to obtain the acquisition data.

15. The system as recited in claim 11, wherein the transmitted acquisition data comprises timestamps, Doppler, and phase shift information.

16. A non-transitory machine-readable storage medium including instructions that, when executed by a machine, cause the machine to perform operations comprising:

collecting, by one or more processors of a computing device, raw global positioning system (GPS) signals for a plurality of positions;

storing in memory, by the computing device, the raw GPS signals for the plurality of positions;

processing the raw GPS signals in batch mode at the computing device to obtain acquisition data for the plurality of positions, the processing further comprising;

identifying, by the one or more processors, a plurality of tasks for parallel processing by a graphics processing unit (GPU);

performing, by the GPU, the plurality of tasks in parallel by assigning each of the tasks to a core processor within the GPU; and

combining, by the one or more processors, results from performing the plurality of tasks to obtain the acquisition data; and

transmitting, by the one or more processors, the acquisition data to a server for calculating locations for the plurality of positions at the server, the server storing the locations and making the locations available for location-tracking applications.

17. The machine-readable storage medium as recited in claim 16, wherein the machine further performs operations comprising:

waking up the GPU before processing the plurality of tasks; and

putting the GPU to sleep after obtaining the acquisition data.

18. The machine-readable storage medium as recited in claim 16, wherein processing the raw GPS signals comprises a parallel code search, wherein the parallel code search comprises:

mixing an incoming signal to baseband and an in-phase signal, where quadrature components are used as real and imaginary inputs when calculating a DFT by performing a fast Fourier transform (FFT) to obtain a first result; and

multiplying the first result by a complex conjugate of DFT of a PRN code generated by a PRN code generator to obtain a second result.

19. The machine-readable storage medium as recited in claim 18, wherein the parallel code search further comprises:

performing an inverse fast Fourier transform (IFFT) of the second result to obtain a third result; and

obtaining a square of the third result to obtain the acquisition data.

20. The machine-readable storage medium as recited in claim 16, wherein the transmitted acquisition data comprises timestamps, Doppler, and phase shift information.