The autonomous navigation of UAS requires, among others, detect-and-avoid capability as a prerequisite for enabling wide-ranging applications, including the transportation of goods and people. This article presents the design, implementation, and experimental results of a UAS-borne radar system detecting drones. The applications of the proposed system include not only detect-and-avoid systems for safe and autonomous navigation of unmanned aircraft systems but also airborne surveillance of malicious drones in controlled or restricted airspace for mitigating security and privacy threats. The system performance in terms of maximum detection range is evaluated through field tests. The experimental results show that the proposed UAS-borne radar can detect a DJI Phantom 4 and a DJI Matrice 600 Pro at a maximum distance of 440 and 500 meters, respectively. The article also provides insights into the system implementation and integration aspects, discusses future research direction, and stresses the need for standardization efforts to benchmark the required performance levels for UAS-borne radars.

Several location-aware applications rely on the position estimated by means of Global Navigation Satellite Systems (GNSS), which are known to estimate an accurate position in an open environment. However, the quality of the estimated position is degraded in harsh environments in terms of accuracy and reliability. Liability-critical services, such as location-based charging, transportation, and road tolling, are threatened by the use of an unreliable position of the user, and the level of trust in the estimated position has to be considered to avoid a failure of the full service chain. Such an issue is faced by means of integrity monitoring methods in the field of GNSS. However, when dealing with harsh environments, integrity monitoring techniques designed for aeronautical applications would lead to very conservative results and to the rejection of all the positions obtained. Such conservative approach is based on the theoretical error models for the estimation of the pseudorange standard deviation in open sky. The purpose of this work is to propose an innovative method for estimating the pseudorange standard deviation extrapolating it from measurements of observable data, to assess the confidence level in the obtained positions in relation to the real environment surrounding the user. While measuring the pseudorange standard deviation taking into account environment conditions and receiver accuracy, the user is able to achieve better estimation of the user equivalent range error (UERE). Estimating the UERE from raw pseudorange measurements with the proposed run-time method and its subsequent use in the computation of protection levels using the receiver autonomous integrity monitoring (RAIM) algorithm shows significant improvement in navigation system availability by deriving tight protection levels.

Uplink power control is a key radio resource management feature in the 3GPP Long Term Evolution (LTE). In order to adapt to changes in the inter-cell interference situation or to correct power amplifier errors, closed-loop adjustments should be applied. In this paper the performance of closed loop power control combined with fractional path loss compensation factor is studied, and an optimal value for the path loss compensation factor is investigated. The closed loop power control with fractional path loss compensation factor is found to improve the system performance in terms of mean bit rate by 68% and utilizes the battery power more effectively.