Integrated navigation approaches of vehicle aided by the strapdown celestial angles

Abstract

The integrated navigation method based on star sensor celestial angles (altitude angle and azimuth angle) is proposed to serve the need for rapidly responsive, reliable, and precise of a hypersonic vehicle under a sophisticated environment. An integrated navigation algorithm suitable for large azimuth misalignment is established under launching point inertial coordinate and local geographical coordinate system based on altitude angle and azimuth angles. Meanwhile, a Bayesian method for data dropouts aided by the strapdown celestial angles is presented for the rapid variability in the celestial star angle with active galaxies. A nonlinear Bayesian filter is applied to implement the simulation on account of the nonlinear feature of the state and measurement equations. The simulation results showed that the Bayesian method for integrated navigation data dropouts could be accomplished by altitude angle and azimuth angle aiding in both launching point inertial coordinate and local geographical coordinate systems, which converge to 1′ in 10 s. The method indicated that the integrated navigation significant errors derived from initial localization and initial attitude alignment could be modified by the strapdown inertial navigation system (SINS) supported by the star sensor’s celestial angle in the local geographic coordinate system in the early launch stage. For the seconds of the flight phase, the integrated navigation aided by celestial angles in the launching point inertial coordinate system was guaranteed for the feasibility and validity. During the flight, the feasibility and validity of integrated navigation were guaranteed aided by celestial angles in launching point inertial coordinate system.

Autonomous Navigation of Unmanned Aircraft Using Space Target LOS Measurements and QLEKF

“…To enhance the navigation performance, many researchers have focused on other autonomous navigation approaches [12][13][14][15][16]. A typical method is INS/CNS integration, where the accumulated errors of the gyroscopes in the IMU are compensated by the measurements of star sensors mounted on the aircraft [17][18][19]. Compared with the GNSS, one of the main characteristics of INS/CNS integrated navigation is that it relies on the optical signals from celestial bodies, such that the high-autonomous and anti-disturbance abilities of the navigation system are retained.…”

Collaborative Multiple UAVs Navigation With GPS/INS/UWB Jammers Using Sigma Point Belief Propagation

“…In our prior work [ 21 ], the Gaussian filter framework with intermittent measurements [22] was established, and the sequence of conditional error covariance was proved to be stochastically bounded. In this paper, the techniques address the message passing scheme on belief propagation with measurement jammers.…”