Nowadays, there is a crucial need to have an enhanced separation for air traffic to cope with the increase in the flight numbers which requires precise determination of aircraft location. Existing traditional surveillance technologies are not suitable for precise positioning of aircraft, and so, cannot guarantee the requirements for next-generation surveillance systems. Automatic Dependent Surveillance-Broadcast (ADS-B) technology has been used recently to accurately find the position of aircraft. Unfortunately, this new technology suffers from potential cyber-attacks, such as spoofing and jamming. To check the trust of ADS-B data and enhance the position of aircraft, Multilateration /ADS-B data fusion is utilized. Unfortunately, the existing localization verification techniques are not accurately suitable for spoofing detection. Likewise, cryptographic methods that use encryption methods require changing the ADS-B protocol and so, changing the current fleet. In contrast, this paper presents a highly accurate and trusted surveillance framework that accurately detects potential spoofing attacks in ADS-B. Furthermore, the proposed framework uses data fusion of available trusted surveillance sensors, dynamic models of aircraft, and flight information systems to achieve a very accurate surveillance system to be used for next-generation surveillance systems. Our results show that the proposed framework significantly detects the various kinds of spoofing attacks, such as constant/frog-boiling attacks. The localization accuracy of aircraft obtained from our proposed framework is improved by 49% and 49% compared to ADS-B and multilateration, respectively. Furthermore, the detection percentage of constant spoofing and frog-boiling attacks are 97% and 93%, respectively.