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This article discusses a new GNSS signal tracking architecture with a quasi-open tracking loop. Matched filtering is adopted for PRN code phase discrimination and FFT is used for frequency discrimination, which greatly shortens the duration of the pull-in step after acquisition. There is no loop filter any more. The discrimination results are fed back to code NCO and carrier NCO directly to modify the local signal in the next round. A Chirp-Z Transform (CZT) algorithm is considered for further improving the frequency resolution of FFT, which can also be computed using FFT. All the modules in this architecture are realized on hardware platform, showing characteristic advantages compared to traditional software tracking loop. Introduction In traditional tracking loop, carrier frequency and code phase of local signal is slowly and finely tuned by the discriminators and the loop filters. But this on the other hand reflects the drawbacks of traditional tracking loop that it takes relatively long time for the loop to recover from interference as well as the acquisition-to-tracking transition, i.e. pull-in stage. So it limits the flexibility of the loop. Matched filtering and FFT algorithm is first put forward for fast acquisition [1]. But the parallel processing it is based on can also be applied in tracking [2]-[4]. It discriminates carrier frequency and code phase directly so that the modified quantity is elastic. Even if the frequency or code phase shifting is large, it still guarantees high adjusting speed. The whole structure can be realized on hardware, which saves the resources used for integrating a CPU on chip and accelerates the computing speed. Moreover, the tracking FFT module can multiplex the FFT module used in acquisition stage. So it won’t take too many resources. The main worry of the tracking structure in question is the frequency tracking precision because FFT is discrete. It is unpractical to do ultra long FFT, which takes too many resources and will cause the chip’s area too large. The fact is that only the acquisition needs to search full spectrum. Tracking needs only searching the spectrum around the estimated frequency from acquisition. So spectrum refining methods should be introduced. There are several kinds of approaches to refine spectrum, such as some linear or nonlinear interpolation algorithms, Zoom-FFT and CZT [3], [5]. Simple interpolations may be too stiff with characteristics of frequency domain not been considered, and the algorithms’ performances are difficult to assess. According to [5], CZT outperforms Zoom-FFT in not requiring filter and higher precision. Tracking Structure Acquisition. For better comprehension, it is necessary to introduce the acquisition method first, because tracking structure is built based on acquisition structure. In acquisition stage, matched filter and FFT is used for search in code phase dimension and frequency dimension respectively [1]. For GPS L1 signal, 10 mmmm 128 mm FFT is chosen to achieve a balance between performance and computing load. The acquisition process can be divided into following steps (Fig.1): Suppose that the PRN number is already known (ignore the search in PRN dimension) and the sampling rate is ffss, local code NCO generates the 10 mmmm corresponding PRN code, the length of which is 0.01 ∗ ffss mm. 3rd International Conference on Machinery, Materials and Information Technology Applications (ICMMITA 2015) © 2015. The authors Published by Atlantis Press 1624 Local PRN Code Phase shifting Down Sampling ⊗ ⊗ ⊗ ... ⊗ ⊗ ⊗ ... 128-dot FFT Down Sampling

FFT-based Fast-Response Quasi-Open Tracking Loop for GPS Receiver