# Joint Radar-Communication Optimization of Distributed Airborne Radar for AOA Localization
## 1 Introduction
In general, the problem of target localization (or tracking) can be analytically characterized by deriving the Cramer-Rao lower bound (CRLB) for target location estimation, thereby facilitating the construction of an objective function for optimization. At present, most of the current research on distributed radar resource allocation focuses on the joint optimization of multiple parameters within a radar system in the context of localization (or tracking). For example, [PERSON] et al. proposed a joint resource allocation scheme involving the sensor subset, power, and bandwidth. By deriving Bayesian CRLB as the objective function for optimization, the power and bandwidth allocation were both optimized using the convex approximation method of sequence parameters [28]. [PERSON] et al. jointly optimized the flight velocity, heading angle, radiation power, signal bandwidth, etc. The proposed method was compared with the following four algorithms: Fixed Path Planning and Optimal Transmit Resource Scheduling, Cooperative Online Path Planning and Transmit Parameter Optimization, Cooperative Online Path Planning and Waveform Parameter Selection, and Online Path Planning and Fixed Transmit Resource Scheduling. The simulation results showed that the algorithm proposed in this article could effectively improve target tracking accuracy while meeting the radio frequency (RF) stealth performance of various airborne radars [29]. In the context of distributed radar localization, [PERSON] et al. jointly optimized the power allocation, bandwidth allocation, and radar node selection in the context of distributed radar localization [30]. [PERSON] et al. proposed a joint subarray selection and power allocation (JSSPA) policy for large-scale distributed MIMO radar networks when tracking multiple targets in cluttered environments. Based on the information of the recursive tracking method, optimal resource allocation could be achieved, aiming to improve tracking accuracy [31]. From the above research status, it can be concluded that the current research on distributed radar resource allocation is usually characterized by the following features: 1. The optimization objective is usually the CRLB of the estimated target location. 2. The main optimization variables are electromagnetic parameters and geographic parameters in the radar domain. The electromagnetic parameters here refer to parameters such as the radar power, waveform, bandwidth, etc., while geographic parameters mainly refer to the location of UAVs. However, these methods for distributed radar resource allocation may incur significant problems when directly applied to airborne radar platforms. The biggest difference between DAR and DGBR is that DAR achieves information transmission and instruction distribution through wireless communication, and stable wireless communication is the prerequisite and foundation for airborne radar to perform tasks. In this context, UAVs need to maximize radar detection performance while meeting system communication performance constraints. As radar and communication resources both belong to the electromagnetic domain, the joint planning of radar and communication systems is a significant research field. The current research rarely involves this field, which means that the effective planning and utilization of electromagnetic domain resources in airborne radar systems have not been achieved. This may result in the loss of radar detection performance or the failure of the UAV swarm to fully meet communication performance constraints during the whole process of mission execution. Currently, very few research studies, represented by [PERSON] et al. from the University of South Australia, have considered communication constraints in DAR localization systems. For example, they modeled the communication range as an area surrounded by a circle that is centered around the UAV itself [31; 32; 33]. When the UAV communicates with other UAVs, they fuse the target location information received by the UAV.