Lu Yin

A novel acquisition scheme for Galileo E1 OS signals

CBOC is the final choice of Galileo E1 OS signal. It is a result of multiplexing BOC(6,1) with BOC(1,1). It has a main drawback that is the autocorrelation function has multiple side-peaks, which will lead to ambiguous acquisition. In this paper we propose a novel method to accomplish unambiguous acquisition. The acquisition scheme is first described, and the mathematical model is introduced. Finally, the performance of this method is analyzed. This method shows very good and interesting results, cancelling the side peaks of the autocorrelation function completely and decreasing the total acquisition time especially in the case the Doppler frequency step is very small.

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

The Lenstra-Lenstra-Lovász (LLL) lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO) communication systems and carrier phase positioning in global navigation satellite system (GNSS) to solve the integer least squares (ILS) problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL), expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm.

Cooperative indoor positioning with factor graph based on FIM for wireless sensor network

Abstract In this paper, we propose a novel cooperative positioning algorithm that fuses information from anchor nodes and neighboring agent nodes, which is suitable for internet of things and robot applications. The mathematical formulation of the cooperative localization problem with factor graph based on Fisher Information Matrix (FIM) theory is presented. We examine the information from an agent node to its neighboring nodes with FIM to evaluate the ranging performance. From this, we will develop the Bayesian inference on factor graph and FIM that will be applied for cooperative positioning. Through simulations, we examine the Cramer–Rao lower bound (CRLB)of the proposed algorithm and how estimation performance is affected by the geometric distributions of anchor nodes and neighboring nodes. Finally, we demonstrate the efficacy and accuracy of our algorithm with multiple anchor nodes and agent nodes.

Relative entropy-based Kalman filter for seamless indoor/outdoor multi-source fusion positioning with INS/TC-OFDM/GNSS

The current single data source positioning navigation systems cannot meet the high precision and high reliability required for indoor/outdoor positioning service. In this study, based on an inertial navigation system, time-and-code division-orthogonal frequency division multiplexing ranging technology and a global navigation satellite system, a relative entropy-based Kalman multi-source fusion positioning model is developed. First, multi-source numerical observation data are filtered, and the outliers are processed in data layers to improve data source reliability and to extract stable observation data. Next, the degree of the multi-source data coupling is quantified in an information layer to analyze the multi-source information coupling degree and to develop a coupling degree factor and a Kalman fusion positioning model for multi-source heterogeneous information. Tests show that this method significantly improves system positioning, navigation stability and positioning precision.

An Unambiguous Tracking Technique for Sine-BOC(kn,n) Modulated GNSS Signals

Binary offset carrier modulation is applied in several signals of the global navigation satellite system (GNSS). It enhanced the robustness of GNSS against the impact of multipath and make the compatibility of GNSS better. However, it has the main drawback of potentially giving biased measurements in acquisition and tracking. The technique we proposed is based on linear fitting with multi-correlator to accomplish unambiguous tracking. The coefficient of each correlator was deduced in this paper. The theoretical analysis and simulation results indicate that the proposed method can performs well on multipath and thermal noise.

Efficient and Robust Convex Relaxation Methods for Hybrid TOA/AOA Indoor Localization

In this chapter, we proposed a hybrid positioning method based on convex relaxation with time of arrival (TOA) and angle of arrival (AOA) measurements. Traditional maximum likelihood (ML) formulation for indoor localization is a nonconvex optimization problem. We exploit the relaxation methods to provide efficient convex solution. Besides, we apply this method to localization with hybrid TOA/AOA measurements firstly and the linear Cramer-Rao Bounds in the scenarios of error-free and erroneous location of sensor nodes are deduced, respectively. Simulations based on TC-OFDM signal system show that the proposed method is efficient and more robust as compared to the existing ML estimation and TOA or AOA based convex relaxation with or without error of sensor nodes location.

Characteristic Analysis and Fast Adaptive Synchronization Algorithm of GPS CNAV-2 Navigation Message Synchronization Code

In the navigation data processing, the speed and accuracy of the frame synchronization processing plays an important role in system efficiency and signal analysis. Unlike other navigation message which synchronized using a fixed sequence, In GPS L1C CNAV-2 navigation message, and the synchronization code uses the BCH (51, 8) code based TOI (Time of Interval) and is no longer fixed binary sequence. The TOI, in GPS L1C CNAV-2 navigation message, is the 18 s count value in every 2 h while indicated by ITOW (Interval Time of Week) and cyclically changes between 0 and 399. Thus, the BCH coding generated by the TOI is circular. Thus, the synchronization algorithm used in fixed binary sequence does not work anymore. Beside, circularity makes us have to count maximum correlation in the two adjacent frames simultaneously and traversal 256 pairs of sequences at last in each detection, which influence the speed of the frame detection and the real timeliness of receiver. To solve this problem, beginning with the shift registers which generate synchronized code of GPS L1C CNAV-2 navigation message, this paper analysis the three characteristics of the loop resistance, autocorrelation, and cross-correlation. Then, the paper designs the fast adaptive synchronization algorithm for GPS L1C CNAV-2 navigation message. In this synchronization algorithm, the first step is estimating the number of error bit in the front nine bit of 52 bit, an integral BCH coding. Then, filter and sort these possible pairs of sequences. When we count the maximum correlation in the two adjacent frames simultaneously, the pairs of sequences is detected based on the priority order. Thus, the fast adaptive synchronization algorithm makes the fast synchronization and low rate of false synchronization in different signal conditions.

Improved Satellite Selection Algorithm Based on Carrier-to-Noise Ratio and Geometric Dilution of Precision

Based on the traditional fuzzy arithmetic and concerned about the influence of carrier-to-noise ratio (C/N0) to positioning accuracy, this paper proposes an improved satellite selection algorithm based on C/N0 and geometric dilution of precision (GDOP). Positioning accuracy is mainly influenced by GDOP and the error of pseudo range measurement, and C/N0 is one of the primer factors influence the latter one. Both the error of pseudo range measurement and GDOP should be concerned in order to decrease the positioning error, instead of separate consideration. Traditional satellite selection algorithms, such as the algorithm of minimum GDOP, the algorithm of max volume of tetrahedron and so on, they just concentrated on the influence of GDOP and ignore the error of pseudo range measurement. This paper chooses the first two satellites with the highest and lowest elevation angle based on the principle of minimum GDOP, and then consider C/N0 and the satellite geometric distribution both when choosing the others. Use fuzzy satellite selection algorithm based on entropy method to weight the two factors. Pick out the satellite combination with smaller GDOP and higher C/N0 in the end. Compare and analyze the two results separately get from the method proposed in this paper and the traditional one, the simulation result shows that the improved satellite selection algorithm that considered GDOP and C/N0 both, compared to the traditional ones, can lead to smaller positioning error and better positioning result.

A BOC Signal Synchronization Algorithm Based on TK Operator

The binary phase shift keying (BPSK) modulation method is generally utilized for the traditional navigation satellite systems; however, the new generation of GNSS, such as modernized GPS, European Galileo, Chinese Compass, etc., will apply binary offset carrier (BOC) modulation technique, which can efficiently split the spectrums of navigation signals using the same frequency so as to reduce the interferences among different systems. But the autocorrelation function of BOC modulated signals has the drawback of multimodality, so it’s very hard to synchronize to the right peak when acquiring and tracking signals, especially under low SNR circumstances, which can decrease the positioning accuracy and even lead to wrong positioning results. A BOC modulated signal synchronization algorithm based on TK (Teager-Kaiser) operator is proposed in this article, which could eliminate all the other peaks in autocorrelation function of BOC modulated signals, and create an ideal curve with only one right peak. As a result, this method could avoid the false lock of code phase and guarantee the high precision fix results.

A Multipath Cancellation Method Based on TK Operator for BOC Signals

The new generation of global navigation satellite systems will apply binary offset carrier (BOC) modulation technique, which can efficiently split the spectrums of navigation signals using the same frequency so as to reduce the interferences among different systems. But the autocorrelation function of BOC modulated signals has the drawback of multimodality, so it’s very hard to synchronize to the right peak when acquiring and tracking signals, especially under low SNR circumstances, which can decrease the positioning accuracy and even lead to wrong positioning results. Meanwhile, if there are multipath signals mixed in the receiving signal, the autocorrelation curve will be greatly distorted, and the number of side-peak will also increase exaggeratedly, which could deteriorate the situation mentioned above. A multipath cancellation method based on TK (Teager-Kaiser) operator is proposed in this article, which could not only detect the right peak in the autocorrelation curve, but also eliminate all the other multipath signals. As a result, this method could avoid the false lock of code phase and guarantee the high precision fix results.