This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is developed that is updated in real-time with a horizon of three waypoints. The purpose of DWN is to overcome a problem that we find in existing WN for small-class fixed-wing unmanned aerial vehicles (UAV) of not accurately reaching waypoints. This problem results at times in high overshoot and, in the presence of wind disturbances, it can cause a vehicle to miss the waypoint and swirl around it. To prevent this, the DWN creates "new waypoints" that are in the background, called turning points. Examples illustrate the improvement of the performance of WN achieved using the DWN algorithm in terms of the targeting of waypoints while reducing fuel and time.
Aiming at the non-stationary characteristics of narrowband radar echo of micro-motion target, a novel micro-motion signal denoising algorithm is proposed. Firstly, the weight function is constructed by coherent accumulation, and the echo is weighted by weight function to filter out the noise in range dimension. Secondly, the singular spectrum analysis(SSA) is performed on the range bin of the echo, the signal with large singularities is preserved, and the noise with small singularities is filtered out. Then, the azimuth dimension signal transformed from time domain into time-frequency domain, the step iteration method is used to adaptively filter the time-frequency spectrum and the time-frequency filtering result with the best denoising effect selected by defining the risk function. Finally, the simulation verify the effect of the proposed method.
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