长码直扩信号扩频序列估计方法研究

项目名称： 长码直扩信号扩频序列估计方法研究

项目编号： No.61201282

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 张花国

作者单位： 电子科技大学

项目金额： 27万元

中文摘要： 本项目旨在研究非合作长码直扩通信信号盲估计的理论问题。针对低信噪比条件下的长码直扩信号，在深入分析其信号数学模型基础上，开展扩频波形估计CRB(克拉美劳界)的理论研究，为衡量各种估计方法的性能提供理论下界和标准；建立单用户条件下扩频序列极大似然估计的理论模型，得到其最优理论估计器，并利用半定规划理论实现该极大似然估计的近似求解；多用户条件下通过将长码直扩信号建模为短码直扩信号的缺失数据模型，利用缺失数据分析与估计理论实现用户个数和各用户扩频序列的精确估计。本项目将为低信噪比条件下长码直扩信号的扩频序列估计提供理论基础与实现算法，最终为非合作通信领域以及其它相关领域的技术研究提供理论与方法。

中文关键词： 长码直扩信号；克拉美劳界；极大似然；半定规划；缺失数据模型

英文摘要： The theoretical problem of blind estimation of long-code direct sequence spread spectrum (DSSS) signals in non-cooperative context is studied in this project. Based on deeply analyzing the mathematical model of long-code DSSS signals at low signal to noise ratio (SNR), the theoretic investigation on the CraméRao bound (CRB) for the spreading waveform estimation problem is researched. The CRB can provide a performance lower bound and performance evaluation standard for various methods. For single-user long-code DSSS signals, we derive the theoretic optimal estimator by building the maximum likelihood estimate (MLE) model of spreading sequence, and exploit the semidefinite programming theory to approximately solve the MLE problem. Under multi-user conditions, based on the long-code DS-SS signals being represented as the short-code ones with missing data, we obtain the accurate estimation of user number and all users' spreading sequences by using the missing data analysis and estimation theory. The project will provide the theoretical basis and realized algorithm for the spreading sequence estimation of long-code DSSS signals at low SNR, and finally provide theory and methods for the study on the non-cooperative communication and other related fields.

英文关键词： Long-code Direct Sequence Spread Spectrum Signals；CraméRao Bound；Maximum Likelihood；Semidefinite Programming；Missing-data Model