基于CA-CFAR桥梁振动目标位置及频率检测方法

雷达在桥梁健康检测领域已经成为最主要的工具之一，主要因为其非接触性、以及可连续，全面检测等优势，雷达对桥梁健康的检测主要通过对桥梁所产生的振动信号进行分析，雷达振动信号包含相位信息，方便对形变量进行提取。对振动信号的检测，通常需要对原始信号进行形变反演，在反演后的信号上再对振动信号进行检测，但是桥梁振动信号通常处于复杂环境中，在杂波以及噪声的影响下，反演后的信号难以呈现振动信号本身的特征，不易进行检测。因此本文提出基于CA-CFAR的桥梁频率检测方法，先在距离多普勒域对距离单元进行检测，再基于振动信号自身具有周期性、多次谐波的特征对信号频率进行检测，本文的方法直接对雷达信号进行频率检测，减少了形变量反演所造成的误差。首先给出了振动信号几何模型以及信号模型。然后论述了检测算法原理。最后通过实验对算法的可行性进行了验证。 

Based on the CA-CFAR bridge vibration target location and frequency detection method

Radar has become one of the most important tools in the field of bridge health detection, mainly because of its non-contact, continuous, comprehensive detection and other advantages. Radar detection of bridge health mainly through the analysis of bridge vibration signals, radar vibration signals contain phase information, easy to extract shape variables. For the detection of vibration signals, it is usually necessary to carry out deformation inversion of the original signal and then detect the vibration signal on the inversion signal, but the bridge vibration signal is usually in a complex environment. Under the influence of clutter and noise, the inversion signal is difficult to show the characteristics of vibration signal itself. hence, this paper proposes a bridge frequency detection method based on CA-CFAR, which first detects the distance element in the distance doppler domain, and then detects the signal frequency based on the characteristic that the vibration signal itself has periodicity and multiple harmonics. the method in this paper directly detects the frequency of radar signal and reduces the error caused by the inversion of shape variables. First, the geometric model of vibration signal and the signal model are given. Then the principle of detection algorithm is discussed. Finally, the feasibility of the algorithm is verified by experiments.