# Joint Radar-Communication Optimization of Distributed Airborne Radar for AOA Localization
## 1 Introduction  
In recent years, radars have faced increasingly complex detection environments with the continuous development of target stealth and electronic warfare technology [1, 2, 3]. Among them, the development of target stealth technology has made the radar cross section (RCS) of targets continuously smaller, making it difficult for traditional radar to detect these targets [4, 5]. Meanwhile, the development of electronic warfare technology has led to a rapid increase in the number of various suppression and deception jamming devices [6, 7]. This has generated an increasingly crowded spectrum environment faced by traditional radars. Radar must choose appropriate frequency bands to smoothly carry out detection tasks. In this context, the detection ability of traditional single ground-based radar (GBR) further decreases for low-altitude flying targets with a slow velocity [8]. In order to address the aforementioned challenges, the DGBR radar is developing rapidly. Compared to a single radar, DGBR cannot only detect targets from multiple views but also effectively integrate the radars of different frequency bands, polarization modes, and signalbandwidths, achieving a stronger detection performance than a simple combination of single radars [9; 10; 11]. However, due to the fact that large GBR is always fixed on the ground, the detection view of low-altitude targets is limited. Moreover, due to the fixed location of GBR (i.e., optimal location deployment cannot be achieved), target detection performance is usually limited. In order to overcome these shortcomings, traditional DGBR usually applies methods such as increasing transmission power [12], increasing antenna aperture [13], and increasing signal bandwidth to enhance detection capabilities [14]. However, these methods often lead to a rapid increase in the volume of radar equipment, resulting in the further deterioration of radar maneuverability. Meanwhile, it can lead to serious problems, such as a rapid increase in the overall manufacturing costs of the radar system and difficulties in later maintenance [15]. DAR is a revolutionary technology aimed at traditional DBGR [16; 17; 18], which is usually of the following advantages: 1. DAR is of more degrees of freedom. DAR can achieve the flexible deployment of radar by flexibly adjusting the locations of the UAVs [19]. This not only enables the more effective detection of targets from multiple angles but also effectively avoids external jamming and attacks [20]. For example, when some nodes in the network are paralyzed by the external jamming of an attack, other UAVs in the network can automatically continue to perform tasks, which greatly improves the robustness of radar networking. 2. DAR is of a better detection view on target. Compared to large DGBRs, DAR typically performs tasks at higher altitudes. High platforms can overcome the weakness of a limited line-of-sight (LOS) of DGBR, making air detection less susceptible to interference from ground clutter and increasing the probability of target detection [21]. 3. DAR is of stronger scalability. Large DGBR can usually only achieve overall system scalability by enhancing the performance (power, antenna aperture, etc.) of each radar in the network, which is easily constrained by the hardware conditions of the radar itself. DAR can flexibly increase or reduce the number of UAVs according to the task requirements [22], making it easier to achieve scalability. Since DAR is of the above advantages, it has been widely applied in target detection [23], localization [24], tracking [25], recognition [26], imaging [27], and other aspects. The premise for DAR to effectively leverage the above advantages in these tasks is that the radar system can effectively and reasonably allocate its internal resources based on the task requirements.