## 1 Introduction  
Since safety is a big concern in air traffic, particularly regarding the safe integration of unmanned aerial vehicles (UAVs) into airspace [1, 2, 3, 4], the integration of supporting systems and expansion of standards and regulations are topics in continuous development. In the late 2000s, efforts were directed towards reducing the risk of midair collision. These efforts led to the definition of the so-called airborne collision avoidance system (ACAS II). The latter is an on-board supporting system, operating independently of air traffic control (ATC). It monitors the traffic in the surrounding airspace to determine a potential collision risk and alarm the flight crew [5]. As a successor to ACAS II, a family of standards called ACAS X has been introduced and is currently under development. Unlike its predecessor, ACAS X has the ability to process sensing information from different sources [6]. Sensors include cooperative and non-cooperative sensors dedicated to the detect and avoid task, also referred to as sensing and avoidance [7]. The main tasks of the sensors are to provide the slant range, bearing, and altitude of intruders, as these parameters are needed for state estimation. The information gain resulting from combining inputs from multiple sensing systems assures less uncertainty and increases awareness of the surrounding airborne traffic. This ultimately leads to a higher degree of safety in air traffic. ACAS X includes multiple underlying variants for certain classes of aircraft. Examples include the baseline system ACAS Xa, which is the successor to ACAS II and is designed for manned aircraft, and ACAS Xu, which will allow multiple sensor inputs and is optimized for unmanned airborne systems [6; 8]. In addition, numerous 6G initiatives are ongoing in the context of an integrated space-air-ground network [9; 10; 11; 12]. These investigations include UAVs [13; 14]. Bearing information plays a crucial rule in the surveillance of the surrounding aerial space in the current ACAS II and upcoming ACAS X [15]. Direction finding (DF) systems rely traditionally on arrays of monopole antenna elements. Based on the reception delays between the receiving antenna elements, and given the knowledge of the geometry in which the array is arranged, the direction-of-arrival (DoA) of a response from an interrogated transponder can be estimated [16]. A different approach for the purpose of DF utilizes multi-port multi-mode antennas (M\({}^{3}\)PAs) [17]. Based on the theory of characteristic modes [18; 19; 20], M\({}^{3}\)PAs are capable of realizing multiple orthogonal radiation patterns on a single conducting surface [21; 22; 23], hence reducing weight and volume. The utilization of M\({}^{3}\)PAs was investigated in [24; 25; 26; 27; 28; 29] for communication and ultra-high-speed communication, in [27] for IoT applications with the possibility of high connectivity, and in [30; 31; 32] for DF use cases. Furthermore, approaches for joint communication and sensing specifically designed towards integrating M\({}^{3}\)PAs aboard UAVs are presented in [33; 34; 35]. ACAS Xu standards [36] recommend using a directional antenna mounted on the top of the aircraft for directional interrogations of Mode C transponders. An omnidirectional antenna mounted on the bottom of the aircraft is sufficient since the top antenna is preferred for transmitting interrogations. However, a directional antenna on the bottom for Mode S and a traffic alert and collision avoidance system's (TCAS's) broadcast interrogations could optionally be utilized. Considering the aforementioned requirements of ACAS Xu, the ability to radiate simultaneously in both directional and omnidirectional manners, in addition to the DF abilities, M\({}^{3}\)PAs represent an attractive option for integration onboard aircraft, as a part of collision avoidance systems. Hence, a significant amount of interest has recently been directed towards utilizing M\({}^{3}\)PAs for the purpose of solving the DF problem in aerial applications.