## 3 Proposed Approach  
### Situation Awareness Data  
A fundamental aspect of our proposed protocol is that we have access to data that are referred to as _situation awareness (SA) data_. Situation awareness is a critical component in military command and control operations, including flight missions in combat situations. In order to make real-time decisions about tactical maneuvers during a combat flight mission, the pilots must have good and accurate information about both adversary and friendly aircraft. SA data contain such information. In our proposed solution, we work with a three-dimensional Euclidean space. The SA data consist of the following:  
* The \(x\)-position (longitude), \(y\)-position (latitude) and \(z\)-position (altitude) of each friendly aircraft in the current situation;
* The speed in the \(x\)-, \(y\)-, and \(z\)-directions of each friendly aircraft in the current situation;
* The acceleration in the \(x\)-, \(y\)-, and \(z\)-directions of each friendly aircraft in the current situation;
* The \(x\)-, \(y\)-, and \(z\)-positions of each adversary aircraft in the current situation;
* The speed in the \(x\)-, \(y\)-, and \(z\)-directions of each adversary aircraft in the current situation;
* The acceleration in the \(x\)-, \(y\)-, and \(z\)-directions of each adversary aircraft in the current situation. In some cases, the SA data only contain incomplete information regarding adversary aircraft position, usually the bearing (i.e., direction) from own aircraft location. This may be sufficient in our case, but otherwise the range (or distance) may be estimated with some uncertainty, e.g., by triangulation of a number of different observations. In our work, a node has two sources of SA data. The first one is the set of SA sensors integrated with the airborne platform. The sensors have a maximum operational range, outside of which they cannot work reliably. We refer to the acquired sensor data as _local SA_ data. The union of all friendly nodes' local SA data is the totality of environmental knowledge that friendly nodes pose as a group. We refer to this as a _unified SA view_. It is important to keep in mind that although the unified SA view contains more data than available for a single node, it does not provide total SA visibility. Some nodes, friendly or otherwise, can be located so far away that they are not captured in the local SA data of any of the friendly nodes and are thus not available in the unified SA view. Each friendly node strives to obtain the unified SA view through exchange of SA data with friendly nodes. This is the second source of SA data. A node that receives SA data from another friendly node merges that with its own local SA and with previously received SA data from other nodes into something called the _node's SA view_. The merging operation favors local SA data over received SA data. In the ideal case, the node's SA view becomes identical to the unified SA view. However, due to latency, packet loss and nodes out of range, a node's SA view may diverge from the unified SA view. When this happens, it prevents the nodes from converging on a common topological view [18]. This phenomenon can lead to suboptimal routing and strategies should be put in place to alleviate its effects. The local SA data are updated regularly, and each SA datum has a timestamp. However, how often the SA data are updated is not completely defined. The SA data are used to keep track of where all aircraft are at each time. Accordingly, since the SA data are updated at certain intervals, the local aircraft needs to update the positions of the other aircraft in the interval \(t_{i}\) to \(t_{i+1}\), where \(\delta=t_{i+1}-t_{i}\) is the interval between updates/exchanges of the SA data. Based on the SA data, we know the position of all friendly as well as adversary aircraft. In the next step, we can then calculate in which directions we can transmit using directional antennas in order to reach each aircraft directly, provided they are in range to receive the radio signal (Tx range).