| 郝顺义,李建文,卢航,黄国荣.基于ML估计的高动态GNSS信号快速捕获检测方法[J].电子测量与仪器学报,2024,38(8):87-94 |
| 基于ML估计的高动态GNSS信号快速捕获检测方法 |
| Fast detection method for high dynamic GNSS signalacquisition based on ML estimation |
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| DOI： |
| 中文关键词: GNSS 捕获 极大似然 判决门限 虚警率 |
| 英文关键词:GNSS acquisition maximum likelihood decision threshold false alarm rate |
| 基金项目:国家自然科学基金（61573373）项目资助 |
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| Author | Institution |
| Hao Shunyi | Teaching and Research section for Flight Control and Electrical Engineering, Aviation Engineering School, Air Force
Engineering University, Xi′an 710038, China |
| Li Jianwen | Unit 31827 of PLA, Beijing 100195, China |
| Lu Hang | Department of Air Ammunition Support, Air Force Logistics Academy, Xuzhou 221000, China |
| Huang Guorong | Teaching and Research section for Flight Control and Electrical Engineering, Aviation Engineering School, Air Force
Engineering University, Xi′an 710038, China |
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| 摘要点击次数: 23 |
| 全文下载次数: 93 |
| 中文摘要: |
| 针对高动态环境下GNSS因频域带宽增加导致捕获难度增大的问题，分析了接收端数字中频采样信号的传输特性及复基带信号经FFT模块处理后的相关峰的检测，提出了基于极大似然（ML）估计的高动态GNSS信号快速捕获检测方法。首先，根据随机信号的统计理论建立二元假设检验条件，构建了奈曼 皮尔逊准则下的GNSS信号捕获判决门限模型；其次，通过判决量的统计特性对等效高斯白噪声方差进行ML估计，根据其估计值计算捕获判决门限，其中通过虚警率的量化放大处理，解决了判决量样本值的增加带来的估计偏差问题；最后，对不同高动态条件下北斗B3I信号进行了捕获检测仿真实验。结果表明采用ML估计方法确定捕获判决门限从而提高高动态GNSS信号捕获的检测方法对高动态适应范围较宽，其频移捕获精度与SINS信息辅助捕获相当，比序贯检测算法提高约28%以上，相同条件下具有更快的平均捕获检测速度。 |
| 英文摘要: |
| To consider increased difficulties of the GNSS signal acquisition due to a wider range of the frequency bandwidth in high dynamic environment, the transmission characteristics of the numeric intermediate frequency signal in the GNSS receiver was analyzed, as well as the correlation peak detection of the complex baseband signal processed by the FFT module, a fast detection method for high dynamic GNSS signal acquisition based on ML estimation is proposed. Firstly, by the construction of Binary hypothesis testing conditions based on the statistical theory of random signals, an acquisition threshold model was presented using the Neyman Pearson Criterion; Secondly, the variance of equivalent White Gaussian Noise based on ML is estimated by judgment statistical characteristics and an acquisition threshold is calculated from variance estimated value，in the meantime the estimation error caused by increased judgment samples was resolved by means of false alarm rate quantized amplification. Finally, the acquisition detection simulation experiment of Beidou B3I signal was conducted in different high dynamic conditions. The result showed the proposed method have a wider scope of high dynamic adaptive capacity, and the precision accuracy of the acquired doppler frequency shift was on a par with the SINS information aiding method, also increased by more than 28% compared to the sequential detection method, as well as a faster detection speed in the same acquisition condition. |
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