## 1 Introduction  
Vehicular positioning systems are actively used in various fields such as autonomous vehicle driving, production, the distribution industry, and the military [1]. Generally, the Global Positioning System (GPS) [2], which utilizes satellites, is used for the positioning of ground vehicles or aerial vehicles. However, GPS has the disadvantage that the reception signal is weak in complex urban terrain and cannot be used in indoor environments. This is because GPS estimates the location through direct communication between a mobile node and a subset of satellites, and in environments with many obstacles or indoors, where radio reception is not possible, it may not be possible to accurately measure the distance between them due to the straightness of radio waves [3]. Furthermore, the accuracy of GPS is generally less accurate than that of indoor positioning systems. In automotive services that require a high precision for the indoor positioning system, metrics other than GPS are often adopted to meet the strict requirements for accuracy and reliability [4]. In these environments, various vehicular positioning systems that build their own infrastructure to estimate the location or the target are actively used [5]. In particular, the Vehicular Ad hoc Network (VANET) positioning system [6] addressed in this paper is mainly used when performing missions with a specific purpose in a robot or vehicle network or performing support tasks for other vehicles in the swarm. Application examples include positioning for autonomous parking in an underground parking lot, drone shows using a swarm of micro drones, real-time traffic information sharing, various missions using unmanned vehicles in spaces where human have difficulty entering, and smart factories and roads [7]. Vehicular positioning systems can utilize various sensors and wireless signals, such as Inertial-Measurement-Unit (IMU)-based Dead Reckoning (DR) [8], Bluetooth [9], ultrasonic waves [10], WiFi [11], and Ultra-Wideband (UWB) [12]. Among them, UWB is the metric that has recently received the most attention in VANET positioning and is actively used and researched in various fields. Compared to other systems, the UWB positioning system has strengths in various aspects, such as high location estimation accuracy, reasonable configuration price, and high system robustness [13]. Distance-based UWB positioning systems generally use the Time Difference of Arrival (TDOA) [14; 15; 16] and Two-Way Ranging (TWR) [17; 18] in the ranging process, and both methods utilize device timeline data. Distance-based positioning has advantages such as no major constraints on the infrastructure configuration, high accuracy, and no severe interference from multiple paths, but it has a fatal disadvantage in that the location estimation error is greatly affected by distance. Generally, in order to perform n-dimensional positioning, n+1 pieces of distance information are used, and if even one distance has an unexpected value, the overall positioning performance will be seriously degraded. The core strength of the UWB system is high-accuracy positioning based on distance measurement with high time resolution by using pulse waves. In other words, the precise measurement of timestamp, which is the device timeline data, is possible. In missions where positioning accuracy is key, if the transmitting device ID or receiving timestamp data for the UWB signal are unclear or have an error in their values, the probability of the task failing can greatly increase. Even if an attacker with a malicious intent manipulates the data of only one device among the nodes that make up the system, serious degradation of the positioning performance may occur, leading to task failure. As a result, distance-based ad hoc device indoor positioning systems such as UWB systems have the disadvantage of being quite vulnerable to external attacks.