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传统GPS卫星信号捕获门限设定方法在互相关干扰情况下存在较大虚警概率,所以无法捕获弱信号.针对该问题进行分析,在此基础上提出一种针对多颗能量不同卫星同时存在情况下的信号检测模型和概率模型.信号检测模型在相关积分非相干累加基础上引入双门限多次检测,由于在考虑噪声的同时也考虑了互相关干扰对弱信号捕获的影响,其概率模型为非中心χ2分布.在原有的恒虚警门限检测方法基础上,提出考虑强信号互相关干扰对微弱信号检测影响情况下的门限计算方法作为新的门限上限,而将原有的门限计算方法作为门限的下限.在此基础上提出强、弱卫星信号共存时的检测思路,即先用门限上限检测强信号并进行互相关干扰消除处理,再用门限下限判断是否有弱信号存在.采用仿真数据和实际数据针对考虑互相关干扰的门限上限进行实验,并和原有门限方法进行比较,证明在强、弱信号共存情况下原有门限无法检测出卫星信号,而新的门限设定方法可以正常工作,并具有较高的检测概率和较低的虚警概率.
In traditional GPS satellite signal acquisition threshold setting method, there is a large false alarm probability in the case of cross-correlation interference, so we can not capture the weak signal.Analyzing this problem, a new method is proposed for the simultaneous presence of multiple satellites Under the signal detection model and the probability model.The signal detection model introduces double-threshold multiple detection based on the correlation integral incoherent accumulation, considering the influence of the cross-correlation interference on the weak signal acquisition while considering the noise, the probability model is Non-central χ2 distribution.On the basis of the original detection method of constant false alarm threshold, a threshold calculation method considering the influence of strong signal cross-correlation interference on weak signal detection is proposed as a new upper threshold, while the original threshold calculation method is taken as Based on which the strong and weak satellite signal coexistence detection ideas, that is, the first detection of high signal threshold and cross-correlation interference cancellation processing, and then use the threshold to determine whether there is a weak signal to the lower limit.Using the simulation data And actual data for the consideration of cross-interference threshold upper limit of the experiment, and the original threshold method Comparative lines, demonstrated strong, weak signal threshold coexistence of the original satellite signals can not be detected, and the new threshold setting method may work, and has a high probability of detection and low false alarm probability.