Unambiguous Acquisition Algorithm Research Articles

Unambiguous acquisition algorithm based on sub‐correlation functions combination for semi‐integer CPM signals

AbstractDue to the nonlinear nature of continuous phase modulation (CPM), most existing unambiguous acquisition algorithms are ineffective in eliminating the ambiguity threat faced by semi‐integer CPM signals. To address this issue, this letter proposes an unambiguous acquisition algorithm based on sub‐correlation functions combination (SCFC). The main idea of this algorithm is to decompose the first pulse amplitude modulation waveform derived from the Laurent decomposition into sub‐signal waveforms that are appropriate for CPM signals. The final unambiguous function is obtained by combining the autocorrelation function of the received CPM signal with the sub‐correlation functions derived from the sub‐signal waveforms and the received CPM signal. Simulation results demonstrate that the SCFC algorithm can eliminate the ambiguity threat of semi‐integer CPM signals with relatively minor detection loss. Moreover, the proposed algorithm successfully retains a narrow main peak and exhibits superior multipath resistance.

A Novel Unambiguous Acquisition Algorithm Based on Segmentation Reconstruction for BOC(n,n) Signal

In order to improve the frequency band utilization and avoid mutual interference between signals, the BD3 satellite signals adopt Binary Offset Carrier (BOC) modulation. On one hand, BOC modulation has a narrow main peak width and strong anti-interference ability; on the other hand, the phenomenon of false acquisition locking caused by the multi-peak characteristic of BOC modulation itself needs to be resolved. In this context, this paper proposes a new BOC(n,n) unambiguous acquisition algorithm based on segmentation reconstruction. The algorithm is based on splitting the local BOC signal into four parts in each subcarrier period. The branch signal and the received signal are correlated with the received signal to generate four branch correlation signals. After a series of combined reconstructions, the final signal detection function completely eliminates secondary peaks. A simulation shows that the algorithm can completely eliminate the sub-peak interference for the BOC signals modulated by subcarriers with different phase. The characteristics of narrow correlation peak are retained. Experiments show that the proposed algorithm has superior performance in detection probability and peak-to-average ratio.

FFT based unambiguous acquisition method for BOC modulation signal

This paper presents an unambiguous acquisition algorithm for Binary Offset Carrier (BOC) modulation signals, which is adopted by modernized Global Navigation Satellite System (GNSS). By utilizing FFT, the spectrum of BOC signals is derived. This paper proposes an unambiguous acquisition method based on FFT to get rid of the BOC modulation drawback. By utilizing FFT, the spectrum of BOC signal is derived. The up and down sideband are separated in frequency domain by rectangular function, which means sideband filtering. Due to sparsity of filtered BOC spectrum, frequency compression method is proposed to reduce the number of IFFT points. Theoretical and simulation results show that this technique completely removes the ambiguity threat in acquisition process.

A novel acquisition algorithm based on two-dimensional delay estimation for BOC signals

Binary offset carrier (BOC) modulated signals are widely utilized in the new generation global navigation satellite system (GNSS), but the multiple peaks of the correlation function result in the ambiguity of acquisition. In this paper, a novel unambiguous acquisition algorithm is proposed, in which spreading code delay and subcarrier delay are estimated separately in a two-dimensional (2-D) space. Exact explicit expressions of the acquisition detection function based on 2-D estimation is obtained by derivation and simplification. The properties of acquisition function and the performance analysis considering noise are studied. Theoretical analysis and experimental results indicate that the proposed acquisition function completely eliminates ambiguity and it demonstrates a good performance in the terms of detection probability, main peak ratio and complexity.

An Unambiguous Acquisition Algorithm for BOC (n, n) Signal Based on Sub-correlation Combination

An Unambiguous Acquisition Algorithm for BOC (n, n) Signal Based on Sub-correlation Combination

Reconstruction of sub cross-correlation cancellation technique for unambiguous acquisition of BOC(kn,n) signals

In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks, an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique (RSCCT) for BOC(kn, n) signals is proposed. In this paper, the principle of signal decomposition is combined with the traditional acquisition algorithm structure, and then based on the method of reconstructing the correlation function. The method firstly gets the sub-pseudorandom noise (PRN) code by decomposing the local PRN code, then uses BOC(kn, n) and the sub-PRN code cross-correlation to get the sub cross-correlation function. Finally, the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed. The simulation shows that RSCCT can completely eliminate the side peaks of BOC (kn, n) group signals while maintaining the narrow correlation of BOC, and its computational complexity is equivalent to sub carrier phase cancellation (SCPC) and autocorrelation side-peak cancellation technique (ASPeCT), and it reduces the computational complexity relative to BPSK-like. For BOC(n, n), the acquisition sensitivity of RSCCT is 3.25 dB, 0.81 dB and 0.25 dB higher than binary phase shift keying (BPSK)-like, SCPC and ASPeCT at the acquisition probability of 90%, respectively. The peak to average power ratio is 1.91, 3.0 and 3.7 times higher than ASPeCT, SCPC and BPSK-like at SNR = -20 dB, respectively. For BOC(2n, n), the acquisition sensitivity of RSCCT is 5.5 dB, 1.25 dB and 2.69 dB higher than BPSK-like, SCPC and ASPeCT at the acquisition probability of 90%, respectively. The peak to average power ratio is 1.02, 1.68 and 2.12 times higher than ASPeCT, SCPC and BPSK-like at SNR = -20 dB, respectively.

SSCM: An Unambiguous Acquisition Algorithm for CBOC Modulated Signal

Composite binary offset carrier (CBOC) signal has been widely researched in GNSS. The main ingredient of CBOC signal is BOC(1,1) signal. Usually, the acquisition method for BOC(1,1) signal is used to capture CBOC signal, while the research of special acquisition method for CBOC signal is rare. In this letter, according to the principle and characteristics of CBOC signal, a special side-peak cancellation method (SSCM) is proposed and simulated. In this method, two special auxiliary signals are introduced. And the local reference signals are obtained by multiplying the data channel signal and pilot channel signal by the auxiliary signals. The cross-correlation results from the received pilot signal and the two local pilot signals with different auxiliary signals will subtract from one another. Then, side peaks of correlation function and in-band noise of pilot channel are suppressed, while the data channel has the same operation results. At last the outputs of pilot channel and data channel will be added up to make full use of the received signal power. By this way, the acquisition efficiency, accuracy, and adaptability to low signal-to-noise ratio (SNR) conditions for CBOC signal have been improved, alongside possible solution when the GNSS receiver works in a critical environment.

An Unambiguous Acquisition Algorithm Based on Unit Correlation for BOC(n,n) Signal

An Unambiguous Acquisition Algorithm Based on Unit Correlation for BOC(n,n) Signal

A Fast Unambiguous Acquisition Algorithm for BOC-Modulated Signals

This paper proposes a fast unambiguous acquisition technique for binary-offset-carrier (BOC)-modulated signals. We remove the ambiguities (side peaks) of the BOC autocorrelation function (ACF), exploiting a reduced-complexity (real and symmetric) filter composed of only seven nonzero samples. The proposed scheme is applicable to both generic sine- and cosine-phased BOC signals. Theoretical and simulation results show that the proposed method removes the ambiguities in the acquisition problem without requiring an auxiliary signal in the receiver.