## 1 Introduction  
The structural deterioration of bridges could pose life-threatening risks to crossing pedestrians, vehicles, and trains. Consequently, health assessment and monitoring of bridges is of great interest to both authorities and stakeholders. The deterioration of bridges could occur due to flooding, earthquakes, winds, or repeated passing loads. The need to establish efficient methods to monitor bridges is increasing as aging structures have higher possibilities of damage occurrence [1, 2]. In Europe, for example, most bridges were constructed in the post-War era between 1945 and 1965 [3]. In Japan, almost one-third of bridges have been in service for over 50 years [4]. In the United States, there are more than 66,000 structurally deficient bridges which account for 11% of total bridges, and most of the bridges in total are older than 65 years old [5]. Bridge health monitoring refers to the identification of dynamic modal characteristics and damage detection in bridges. Dynamic modal characteristics such as frequency, damping, and mode shapes reflect the physical properties of the structure and can be used in models to assess the health state of the structure. On the other hand, damage detection includes the identification of the existence, location, and severity of damage and, finally, the life expectancy of the structure [6; 7; 8]. It is important to note that the modal properties used for the identification and detection of damage in bridges are influenced by environmental factors such as temperature, which necessitates extensive work to study bridge response under varying temperatures [9; 10]. Direct vibration-based bridge health monitoring is performed by installing a large number of sensors directly on the bridge to record bridge vibrations. Then, the vibration signals are processed to estimate the health state of the bridge [11; 12]; however, it is difficult to implement a direct method on a wide scale for several reasons. First, such a sensory system bears a high cost for equipment and installation. Second, the life expectancy of the sensory system is shorter than that of the bridge itself, so regular maintenance of the system is required. Third, installation could be dangerous for many types of bridges. Fourth, due to limitations regarding sensor locations, accelerometers may not be able to detect remote damage [13; 14]. In 2004, [PERSON] and [PERSON] [15] proposed an indirect vibration-based approach to overcome the issues of direct methods. Their approach employed an instrumented vehicle to record vibration signals while passing over a bridge. The recorded vibrations are then processed in order to assess the health state of the bridge. This indirect method is especially cost effective because it requires one or few sensors to be installed on a vehicle. The sensors could be installed on a typical vehicle [16], or on a special trailer attached to a vehicle [12]. This indirect method is highly mobile because the instrumented vehicle can be used for an unlimited number of bridges. Besides, the passing vehicle scans the vibration of every point of the bridge, unlike the direct method, which is limited to the locations of the sensors. The feasibility of the indirect method has been proven by field test experiments when [PERSON] and [PERSON] [17] extracted the fundamental frequency of a real bridge from a passing vehicle. Since then, the indirect method has attracted the attention of many researchers who are interested in bridge health monitoring. Several techniques have been proposed to obtain higher accuracy and extract higher modes of frequencies when using a scanning vehicle [18; 19; 20]. Also, several methods have been proposed to construct mode shapes for bridges when considering a passing vehicle [21; 22; 23]. Damage detection employing the indirect method has been conducted using several approaches such as wavelet transformation, empirical mode decomposition, and Hilbert-Huang transformation [24; 25; 26; 27].