A Two-step Frequency Offset Estimation Method for Enhanced Telemetry Integrated Network System in Multipath Channel

Abstract

The present invention provides a two-step frequency offset estimation method of an enhancement telemetering integrated network system in a multipath channel. The problems are solved that a classic estimator in the multipath channel cannot consider estimation range and estimation precision at the same time. The implementation scheme of the method comprises the steps of: processing a data sequence employed at a transmitting terminal by a forming excursion quarternary phase-shift keying portion and responding to modulation by the forming excursion quarternary phase-shift keying portion to obtainmodulation information; transmitting the modulated signals through the multipath channel to arrive at a receiving terminal; at the receiving terminal, performing preliminary frequency offset estimation by employing an autocorrelation function of the input signals; and adding the preliminary frequency offset estimation value and a secondary preliminary frequency offset estimation value to obtain afinal carrier frequency offset estimation value. The two-step frequency offset estimation method is low in computing complexity, accurate and reliable in estimation result, considers a large-estimation range and high estimation precision and can be used for an enhancement telemetering integrated network system.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a two-step frequency offset estimation method, which can be used to enhance a telemetering integrated network system. Background technique [0002] Telemetry systems are widely used in aviation, aerospace, ships, weapons and other fields. In recent years, with the rapid development of network technology, the networking, integration, and air-space-ground integration of telemetry systems have become a new development trend. In order to meet the needs of continuous development and change, people are gradually deepening the research on the iNET standard of the enhanced telemetry integrated network. Moreover, due to the rapid development of wireless communications, the shortage of spectrum resources is becoming more and more obvious. In order to solve this problem, the iNET standard uses SOQPSK-TG signals with high spectrum efficiency. [0003] When the SOQ...

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Problems solved by technology

[0004] Most of the estimation algorithms used in the actual communication system simulation are quasi-best estimators based on ML estimation criteria. Among them, the more classic estimation algorithms include Kay algorithm, Fitz algorithm, L&R algorithm and M&M algorithm. The phase difference of the correlation function related to the received signal is used to reduce the complexity of the maximum likelihood estimation algorithm. Although the mean square error of these estimation algorithms can approach the Cramereau boundary CRB under a certain signal-to-noise ratio, it is difficult to simultaneously Taking into account a larger estimation range and a higher estimation accuracy

In the article "Frequency Offset Estimation of Spaceborne AIS Signal Two-step Refinement", a frequency offset estimation algorithm based on two-step refinement of spaceborne AIS signal is proposed. This article analyzes the estimation error of the Fitz algorithm, in a certain To a certain extent, the estimation range and estimation accuracy can be guaranteed, but the estimation range and estimation accuracy are related to the summation items in the correlation function. The more summation items, the better the estimation performance, so the algorithm is increased to a certain extent. the complexity

Meng Qingping and Zhou Xinli proposed an improved Fitz frequency offset estimation algorithm based on autocorrelation function in the article "An Improved Fitz Carrier Frequency Offset Estimation Method and Its Simulation", although this method expands the estimation range of the original Fitz algorithm, but However, it does not improve the estimation accuracy at low SNR

[0005] In addition to the above-mentioned problems, the above estimation algorithms are all discussed under the AWGN channel. Under the complex multi-path fading channel, due to the unknown multi-path interference, these algorithms cannot be used directly.

In 2014, MichaelRice and Erik Perrins et al. used the periodic SOQPSK-TG pilot signal of the iNET structure to derive the corrected estimators of the above classic estimation algorithms in multipath fading channels, and performed simulations. The results show that these algorithms Both can approach the CRB boundary under a certain signal-to-noise ratio, but it is difficult to ensure a large estimation range and a high estimation accuracy at the same time

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