In a GPS-denied environment, even the combination of GPS and Inertial Navigation System (INS) cannot provide location reliably and accurately. We propose a new denoised stereo Visual Odometry VO/INS/GPS integration system for autonomous navigation based on tightly coupled fusion. The presented navigation system can estimate the location of the vehicle in either GPS-denied or low-texture environments. Because of the random walk characteristics of the drift error of the inertial measurement units (IMU), the errors of the states grow with time. To correct these growing errors, a continuous update of observations is necessary. For this purpose, the system state vector is augmented with the extracted features from a stereo camera. Consequently, we utilize the measurements of extracted features from consecutive frames and GPS-derived information to make these updates. Moreover, we apply the discrete wavelet transform (DWT) technique before data fusion to improve the signal-to-noise ratio (SNR) of the inertial sensor measurements and attenuate high-frequency noises while conserving significant information like vehicle motion. To verify the performance of the proposed method, we utilize four flight benchmark datasets with top speeds of 5 m/s, 10 m/s, 15 m/s, and 17.5 m/s, respectively, collected over an airport runway by a quad rotor. The results demonstrate that the proposed VO/INS/GPS navigation system has a superior performance and is more stable than the VO/INS and GPS/INS methods in either GPS-denied or low-texture environments; it outperforms them by approximately 66% and 54%, respectively.

在GPS拒绝的环境中，即使GPS和惯性导航系统（INS）的组合也无法可靠，准确地提供位置。我们提出了一种新的去噪立体视觉测距VO / INS / GPS集成系统，用于基于紧密耦合融合的自主导航。提出的导航系统可以估计GPS拒绝或低纹理环境中车辆的位置。由于惯性测量单元（IMU）的漂移误差具有随机游动特性，因此状态误差会随时间增长。为了纠正这些不断增长的错误，必须不断更新观测结果。为此，系统状态向量将使用从立体摄像机提取的特征进行扩充。所以，我们利用对连续帧中提取的特征的测量结果以及GPS衍生的信息来进行这些更新。此外，我们在数据融合之前应用了离散小波变换（DWT）技术，以改善惯性传感器测量的信噪比（SNR），并衰减高频噪声，同时保留诸如车辆运动之类的重要信息。为了验证所提出方法的性能，我们利用四个飞行基准数据集，分别在机场跑道上通过四边形收集了最高速度分别为5 m / s，10 m / s，15 m / s和17.5 m / s的数据。转子。结果表明，所提出的VO / INS / GPS导航系统在GPS受限或低纹理环境中均具有优于VO / INS和GPS / INS方法的性能，并且更稳定。它的表现要比它们高出约66％和54％，