## 1 Introduction  
A military communication network establishes a wireless communication network to support the rapid deployment of combat forces in emergency situations [1]. During the construction of the communication network, ground communication networks face challenges caused by the obstruction of radio visibility by terrain and man-made structures. For satellite communication networks, although they offer mobility, their data transfer capacity is limited relative to the associated costs, and they are constantly exposed to radio interference. Consequently, there is growing interest in establishing an aviation communication network utilizing aircraft [2]. As aircraft are in constant operation and motion, the antenna system crucial for effectively establishing an aviation communication network must possess rapid beamsteering performance. Additionally, it should be capable of steering the beam in a forward direction based on the azimuth angle criteria. The active phased array antenna system is an antenna system that electronically steers and shapes the beam by adjusting the amplitude and phase of the excited signals from each arrayed radiating element [2; 3; 4; 5; 6; 7; 8]. This allows rapid beam-steering and beam-shaping performance. Additionally, depending on the configuration of the radiating element array, this method enables forward beam steering based on an azimuth-based approach [9; 10; 11]. Therefore, we can conclude that an active phased array antenna system is suitable for establishing aviation communication networks. When in flight, an aircraft is constantly in a state of motion, so its location cannot be determined. To establish an aviation communication network, it is necessary to quickly and accurately detect the location of the communication counterpart. Representative methods of detecting the location of a communication counterpart based on an active phased array antenna include ESPRIT [12; 13; 14], MUSIC [15; 16; 17], heuristic algorithms [18; 19; 20], and the monopulse technique [21; 22; 23]. ESPRIT estimates the precise direction of a signal using multiple antenna arrays. It is based on the principle that signals exhibit unique rotational invariances between different antennas in an array. Thus, ESPRIT assumes that a signal is invariant to the rotation between antennas and utilizes this assumption, along with the relative spacing between antennas, to accurately estimate the direction. This function makes ESPRIT particularly adept at accurately estimating signals in high-density antenna arrays; thus, it is known for its high-resolution nature. However, a disadvantage of ESPRIT is its slow estimated angle calculation due to the large number of eigenvalue decompositions performed [12]. The MUSIC technique uses signals received from a multiple antenna array to generate a spatial spectrum matrix. Through the Singular Value Decomposition (SVD) of the spatial spectrum matrix into eigenvectors and eigenvalues, the MUSIC algorithm calculates its estimated angles. In particular, the MUSIC technique has robust performance in terms of accurately estimating signals, especially in high-density antenna arrays. However, it requires significant computation, such as through the decomposition of training values and the detection of spectra and eigenvalues, resulting in a slow estimated angle calculation [16]. Heuristic algorithms are used to solve complex problems, helping researchers to identify approximate solutions quickly without seeking the optimal solution, as they rely on empirical knowledge. These algorithms typically operate efficiently by following heuristic rules associated with the characteristics of the problem in question. When applying a heuristic algorithm to a specific beamforming problem, the location of the counterpart is estimated by searching for the optimal phase weighting set. However, the estimated location calculation is also slow due to the number of cases considered, which exponentially increases in line with the number of arranged radiation elements [24].