In competing multi-dimensional gaming drones, inherent inaccuracies of the precisepoint-positioning (PPP) measurement of the global navigation satellite system (GNSS) have become rampant, hence, necessitating this work. These inaccuracies, occasioned by system drawbacks such as sudden GPS lock, device misalignment constraints, poor detection and communication signals, all lead to PPP computational complexities. To mitigate the inherent PPP complexities, robust and hybrid accurate continuous-discrete (ACD) cubature-extended Kalman filter (C-EKF) methodology for next-generation GNSS integrated system is corroborated. More precisely, time updates to the state and parameter subvectors were accomplished using the third-degree spherical-radial cubature rule. A testbed deployment of the system was then conducted and investigated using tightly-coupled (i) ring laser gyroscope (RLG) and (ii) micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) based devices to ascertain the PPP cooperative tendencies. Optimized performance comparisons of the proposed hybrid C-EKF over the existing cubature Kalman filter (CKF) and the extended Kalman filter (EKF) schemes with-respect-to (w.r.t) their probabilistic outages, Yaw error-differences and ergodic capacities were demonstrated in situations of inaccurate PPP caused by GNSS distortions.INDEX TERMS Gaming drones, global navigation satellite system (GNSS), inertial measurement unit (IMU), hybrid cubature-extended Kalman filter (C-EKF), precise point positioning (PPP).