Visual navigation for low altitude unmanned aerial vehicles (UAV) shows many scientific and technical challenges in terms of navigation performances, complex 3D environment, high computational requirements for real-time image processing and very limited onboard mass and power resources. The current paper presents a concept of a visual navigation system, based on a wide angle mono camera as vision sensor and matching of the recovered and reference 3D environment, modeled by a digital elevation map (DEM). The recovered 3D models are being produced by real-time optical flow processing of the navigation camera images. An embedded optical correlator is introduced, which allows a robust and ultra high-speed optical flow processing under different and even unfavorable illumination conditions. The proposed concept can be augmented by any state-of-the art navigation aids, e.g. GPS, IMU, magnetometers. The current paper discusses the general principles and structure of the navigation system as a vision only system, i.e. without any additional navigation aids, and with instantaneous determination of the vehicle state, i.e. without time filtering. The paper gives also detailed end-to-end visual navigation performance results, based on a detailed software simulation model of the visual navigation system, including the optical correlator as the key component for ultra-high speed image processing.