International Journal of Navigation and Observation

Volume 2015, Article ID 765898, 12 pages

http://dx.doi.org/10.1155/2015/765898

## FFT Splitting for Improved FPGA-Based Acquisition of GNSS Signals

^{1}Electronics and Signal Processing Laboratory (ESPLAB), École Polytechnique Fédérale de Lausanne (EPFL), 2000 Neuchâtel, Switzerland^{2}Laboratory of Space Technologies, Embedded Systems, Navigation and Avionic (LASSENA), École de Technologie Supérieure (ÉTS), Montréal, QC, Canada H3C 1K3

Received 18 September 2015; Accepted 25 November 2015

Academic Editor: Letizia Lo Presti

Copyright © 2015 Jérôme Leclère et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

With modern global navigation satellite system (GNSS) signals, the FFT-based parallel code search acquisition must handle the frequent sign transitions due to the data or the secondary code. There is a straightforward solution to this problem, which consists in doubling the length of the FFTs, leading to a significant increase of the complexity. The authors already proposed a method to reduce the complexity without impairing the probability of detection. In particular, this led to a 50% memory reduction for an FPGA implementation. In this paper, the authors propose another approach, namely, the splitting of a large FFT into three or five smaller FFTs, providing better performances and higher flexibility. For an FPGA implementation, compared to the previously proposed approach, at the expense of a slight increase of the logic and multiplier resources, the splitting into three and five allows, respectively, a reduction of 40% and 64% of the memory, and of 25% and 37.5% of the processing time. Moreover, with the splitting into three FFTs, the algorithm is applicable for sampling frequencies up to 24.576 MHz for L5 band signals, against 21.846 MHz with the previously proposed algorithm. The algorithm is applied here to the GPS L5 and Galileo E5a, E5b, and E1 signals.

#### 1. Introduction

The question of computing a circular correlation between a local code replica and an incoming code having a bit sign transition is a recurrent problem in global navigation satellite system (GNSS) [1–9]. This problem, already present with the GPS L1 C/A signal, is even more important with the modern GPS and Galileo signals, because of the higher data rate and the presence of the secondary code that imply a potential bit sign transition in each consecutive period of the primary code. This problem appears with the parallel code search (PCS) acquisition method, where a circular correlation is performed through fast Fourier transforms (FFTs) over one period of the primary code [4].

The straightforward solution to this problem is to at least double the length of the sequences, by using more samples of the input signal (to observe at least two code periods and thus to be sure to observe one code period that is free of sign transition) and by zero-padding the local code replica [4, 9]. However, this method implies using longer FFTs, which increases the processing complexity, and at least half of the calculated samples are discarded, making this solution suboptimal.

Note that this straightforward solution is also a solution to other problems. (1) Still with the PCS, the length of the sequences may need to be increased to satisfy a constraint on the FFT length. For example, if the FFT length must be a power of two and if one code period corresponds to 4000 samples, applying directly zero-padding on both incoming and local sequences to get sequences of 4096 samples will result in losses (in general, the zeros will not be inserted at the same position inside the received and local codes; see [10] for more details). To avoid these losses, at least two code periods should be observed in the incoming or local signal. In the previous example, the incoming sequence would thus be composed of 8000 signal samples padded with 192 zeros, whereas the local code would be composed of 4000 samples padded with 4192 zeros. (2) With another acquisition method known as double block zero padding (DBZP) [11, 12], the incoming signal and the local code are cut in small portions and the correlations are computed on these small portions. However, in order to compute correctly the correlation, each portion of the local code is padded with zeros and correlated with two consecutive portions of the incoming signal, as in the straightforward solution.

In this paper, we propose the use of a method to reduce the zero-padding in order to improve the efficiency. The method is based on the fact that an -point FFT can be computed using -point FFTs [13, Section 13.47]. In particular, we focus on the computation of an -point FFT using three -point FFTs or five -point FFTs. This method is applied in other areas (this is used, e.g., in new mobile phone long term evolution technology, where 512-point FFTs are used to compute a 1536-point FFT [14]), but it has not yet been applied to the acquisition of GNSS signals.

The rest of the paper is organized as follows. Section 2 only briefly recalls the problem and the current solutions, since these were already detailed in [4]. Section 3 describes the FFT splitting algorithm. Section 4 evaluates the performance of the proposed algorithm for the acquisition of the L5, E5a, E5b, and E1 signals, in terms of complexity and resources for an FPGA implementation. Finally, Section 5 concludes this paper.

#### 2. Problem and Current Solutions

The signal received from a GNSS satellite contains a spreading code, whose beginning is unknown, and an unknown residual carrier frequency due to the Doppler effect. The aim of the acquisition is to determine the code delay and the carrier frequency for all visible satellites [15]. Among different methods, there is the basic serial search (SS) [16], there are one-dimensional parallel searches such as the parallel frequency search (PFS) and the PCS [16], [22, Chap. 2], and there are two-dimensional parallel searches such as the DBZP method [11, 12] (which is an extension of the PFS) or the methods proposed in [17, 18]. The parallel code search method seems to be among the most attractive methods for the acquisition of modern signals, because it can compensate the code Doppler (especially important with signals having a high chipping rate and with weak signals requiring a long integration) whereas some other methods (such as those based on the PFS) cannot compensate it [19], and one-dimensional parallel methods are less complex to implement than two-dimensional parallel methods.

As mentioned in the introduction, the PCS performs a circular correlation between a local code replica of the satellite searched and the received signal using FFTs, usually over the primary code period. Then, extra coherent integration or noncoherent integration can be performed, as shown in Figure 1 (note that the FFT of the local code could be precomputed and stored in a memory to use only 2 FFTs in real time). If the Doppler frequency is correctly eliminated and if there is no sign transition, a peak will appear at the correct code delay, as illustrated in Figure 2(a). However, in the presence of a sign transition between two consecutive code periods (due to the data or the secondary code), there may be a loss depending on the position of this sign transition in the received signal, as shown in Figures 2(b) and 2(c). Nevertheless, note that when the correlation peak decreases at the correct Doppler frequency bin due to a sign transition, other peaks will appear with a lower amplitude at incorrect Doppler frequency bins [8].