Direct P-code acquisition algorithm based on bidirectional overlap technique

According to the signal-to-noise ratio （SNR） loss of average algorithms in direct P-code acquisition method, this paper analyzes the SNR performance of the overlap average algorithm quantitatively, and derives the relationship of SNR loss with overlap shift value and initial average phase difference in the overlap average algorithm. On this basis, the bidirectional overlap average algorithm based on optimal correlation SNR is proposed. The algorithm maintains SNR consistent in the entire initial average phase difference space, and has a better SNR performance than the overlap average algorithm. The effectiveness of the algorithm is verified by both theoretical analysis and simulation results. The SNR performance of the bidirectional overlap average algorithm is 5 dB better than that of the direct average algorithm, and 2 dB better than that of the overlap average algorithm, which provides the support for direct P-code acquisition in low SNR.

A New Iterate SR Algorithm for Adaptive Multiuser Detection

The sign algorithm has been extensively investigated for digital echo cancellation application and other adaptive filtering applications. In this paper, we use the blind averaging Sign-regressor (SR) algorithm for adaptive multiuser detection. It is another least mean square (LMS) algorithm and eliminates the need for multiplication in the adaptive algorithm. The new algorithm not only reduces the calculation complexity but also has good convergence character. Simulations indicate that this algorithm can adapt to the changes of the environment quickly and improve the stability of the SIR.

Improved direct P code acquisition technique

P code direct acquisition is an important technology in satellite navigation system. As the P code has a long period, it is hard to directly acquire. The traditional average method can process multiple code phases in a time to shorten the acquisition time. But with the increase of average phase error of the input signal and the local code, the correlation signal-to-noise ratio （SNR） loss increases. To reduce the SNR loss, an improved average method is introduced. A new sequence is generated with a summation of phase shifting sequences to decrease correlation peak loss. Simulation results show that compared with direct average method, the improved average method effectively increases correlation SNR.

A weighted averaging method for signal probability of logic circuit combined with reconvergent fan-out structures

By analyzing the structures of circuits,a novel approach for signal probability estimation of very large-scale integration(VLSI)based on the improved weighted averaging algorithm(IWAA)is proposed.Considering the failure probability of the gate,first,the first reconvergent fan-ins corresponding to the reconvergent fan-outs were identified to locate the important signal correlation nodes based on the principle of homologous signal convergence.Secondly,the reconvergent fan-in nodes of the multiple reconverging structure in the circuit were identified by the sensitization path to determine the interference sources to the signal probability calculation.Then,the weighted signal probability was calculated by combining the weighted average approach to correct the signal probability.Finally,the reconvergent fan-out was quantified by the mixed-calculation strategy of signal probability to reduce the impact of multiple reconvergent fan-outs on the accuracy.Simulation results on ISCAS85 benchmarks circuits show that the proposed method has approximate linear time-space consumption with the increase in the number of the gate,and its accuracy is 4.2%higher than that of the IWAA.

Modeling,Oscillation Analysis and Distributed Stabilization Control of Autonomous PV-based Microgrids

Driven by rising energy demand and the goal of carbon neutrality,renewable energy generations(REGs),especially photovoltaic(PV)generations,are widely used in the urban power energy systems.While the intelligent control of microgrids(MG)brings economic and efficient operation,its potential stability problem cannot be ignored.To date,most of the research on modeling,analyzing and enhancing the stability of MG usually assume the DC-link as an ideal voltage source.However,this practice of ignoring the dynamics of DC-link may omit the latent oscillation phenomena of autonomous PV-based MG.First,this paper establishes a complete dynamic model of autonomous PV-based MG including PV panels and DC-link.Different from previous conclusions of idealizing DC-link dynamics,participation factor analysis finds the potential impact of DClink dynamics on system dynamic performance,and different influence factors including critical control parameters and nonlinear V-I output characteristic of PV array are considered to further reveal oscillation mechanisms.Second,based on the average consensus algorithm,a distributed stabilization controller with strong robustness is proposed to enhance stability of the PVbased MG,which does not affect the steady-state performance of the system.Finally,the correctness of all theoretical analysis and the effectiveness of the proposed controller are verified by time domain simulation and hardware-in-loop tests.

Distributed Energy Sharing in Energy Internet Through Distributed Averaging

This paper proposes a distributed averaging iteration algorithm for energy sharing in microgrids of Energy Internet based on common gossip algorithms. This algorithm is completely distributed and only requires communications between neighbors. Through this algorithm, the Energy Internet not only allocates the energy effectively based on the load condition of grids, but also reasonably schedules the energy transmitted between neighboring grids. This study applies theoretical analysis to discuss the condition in which this algorithm can finally reach supply-and-demand balance. Subsequently, the related simulation validates the performance of the algorithm under various conditions.