Unambiguous Tracking Technique Based on Shape Code for BOC Signals

Abstract

The multiple peaks characteristic of binary offset carrier (BOC) autocorrelation function (ACF) makes ambiguity easy to be generated. There are some methods to eliminate ambiguity, but for higher-order BOC Signal, it will sacrifice signal energy or cannot maintain narrow correlation. This paper studies these problems. According to the idea of GRASS algorithm shape code, this paper proposes an unambiguous tracking algorithm, Sub Cross-correlation Shift Technique (SCST), which is suitable for BOC(m,n) signals.The key to this algorithm is to generate a new cross-correlation function between the BOC signal and the PRN code based on the shape code. The new cross-correlation function is linearly combined with the autocorrelation function of the BOC signal to remove sub-peak interference and achieve high-accuracy tracking. The phase discrimination function is given, and the effectiveness of the tracking algorithm is analyzed theoretically. The disadvantage of this method is that it needs multilevel storage, which will bring extra resource consumption to the receiver. For comparison, Unit Correlation, ASPeCT, GRASS, and the algorithm proposed by Yan are proposed. Experiments show that SCST can completely remove the side peak, and the phase discriminator output has only two main peaks, which successfully eliminates the false lock point. The multipath error envelope has only one and the smallest area. In terms of code tracking accuracy, for a BOC(10,5) signal with a received signal-to-noise ratio (SNR) of −28 dB, SCST is less than 45.8%, 67.5%, and 12.2% of the Unit Correlation, GRASS, and Yan proposed algorithms. BOC, tracking, PRN code, unambiguous. INDEX TERMS

Enhanced Synchronization Algorithms for BOC Signals Based on Reconstructed Sub-Correlation Functions

“…The false alarm probability is shown in Equation (30), and the threshold 𝑉 for detection can be obtained from Equation (30). The detection probability can be expressed as Equation (31), where 𝑎 𝜎 ⁄ denotes the signal-tonoise ratio and 𝐼 (𝑥) denotes the first-class zero-order modified Bessel function. As shown in Figure 8, the steps in signal acquisition are as follows:…”

“…Different from the rule of splitting according to the modulation order of the signal in [30,31], we split the signal according to the integer multiple of the modulation order when reconstructing the signal and give its effect on the multipath performance.…”