With the development of unmanned aerial vehicle (UAV) and wireless laser communication technology, as well as the continuous maturity of related devices, UAV laser communication has emerged as the current research hot spot because of its unique advantages in scientific detection, emergency rescue, and military reconnaissance. In UAV laser communication, atmospheric effect (including atmospheric absorption, scattering, and atmospheric turbulence) and pointing error are the two main factors that cause deterioration of link performance. Therefore, establishing a suitable channel model is essential to completely understand the dynamic communication process of UAV laser communication. Existing studies assume that the pointing errors between the communication terminals are identically distributed in the azimuth and elevation directions although they cannot accurately describe the random jitter characteristics of the actual UAV platform. In this study, the pointing characteristics of the oscillating mirror type laser communication terminal are analyzed, whereby a more realistic Hoyt distribution pointing error model is established, to obtain an expression for the joint channel probability density function. The accuracy of the proposed model is verified by numerical simulations and experimental analysis.

To accurately analyze the link performance of laser communication between UAVs, a more realistic Hoyt distribution pointing error model is established. First, the probability distribution of the pointing error angle of the oscillating mirror type laser communication terminal was calculated by using the vector reflection law and the rotation transformation matrix. Furthermore, a joint channel probability density function expression was derived considering atmospheric attenuation, atmospheric turbulence, and pointing error. Subsequently, the effects of different turbulence intensities and different UAV jitter variances on link performance were analyzed. Finally, to verify the correctness of the proposed pointing error model, we tested the pointing error angle of the system using the multi-rotor UAV equipped with laser communication equipment.

The pointing error of the UAV laser communication terminal was tested outdoors. The experimental system consisted of a multi-rotor UAV platform and an oscillating mirror type laser communication terminal (Fig. 6). When the initial azimuth and elevation angles are both zero, the attitude measurement unit on the laser communication terminal, measures the azimuth and elevation angles of the terminal in real-time and obtains the probability distributions of the error angles for the azimuth, elevation, and combined pointing. The results show that the terminal azimuth error angle follows a normal distribution with mean of 0 and standard deviation of 0.4° (Fig. 7); the elevation error angle follows a normal distribution with mean of 0 and standard deviation of 0.05° (Fig. 8); the combined pointing error angle obeys the Hoyt distribution (Fig. 9). The above experimental results were substituted into formula (15), the simulation results are consistent with the experimental data fitting results, which proves the correctness of the pointing error model.

This study investigated the channel model of laser communication between UAVs and proposed a method for solving the pointing error of the oscillating mirror type laser communication terminal. A more realistic Hoyt distribution pointing error model was established to accommodate the different jitter variances of the UAV platform in the azimuth and elevation directions, thereby deriving the probability density function expression of the joint channel. Finally, the pointing error model was verified by numerical simulations and experiments. The experimental results show that the azimuth and elevation pointing error angles of UAV conform to the normal distribution, with mean 0 and standard deviations of 0.4° and 0.05°, respectively. The combined pointing error angle conforms to the Hoyt distribution. The experimental results match the simulation results well, validating the correctness of the pointing error model.