This study presents an active acceleration compensation method for spacecraft rendezvous guidance in very low Earth orbit (VLEO). First, it addresses the challenge of estimating aerodynamic forces in VLEO, which arise from environmental uncertainties and unsteady flow characteristics. To overcome this issue, a novel approach is proposed that integrates an Extended Kalman Filter (EKF) with a Neural Network (NN). This method decomposes the aerodynamic acceleration of space debris into components attributable to tumbling motion and other contributing effects. Finally, the effectiveness of the proposed approach is demonstrated through numerical simulations conducted under one hundred different atmospheric conditions and various initial positions.

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A Japanese group is developing a new vertical take-off and landing rocket for suborbital flights using an air-breathing engine. This study presents the development of a lobed mixer for mixing hydrogen and air in the air-breathing engine. First, two-dimensional models around the lobe are used to evaluate the performance of the lobed mixer. Fundamental experiments are conducted using the models to mix high-temperature helium and room-temperature air, or high-temperature air and room-temperature air. The experimental results show that the mixing of hot air and room-temperature air can simulate the mixing of different gases. Subsequently, the shape of the lobed mixer employed in the engine is determined based on the experimental results. A 1/2 scale sector model of the determined geometry is fabricated, and its performance is evaluated. Finally, an axisymmetric lobed mixer is fabricated and mounted onto the air-breathing engine for static fire testing. The appropriate mixing, ignition, and combustion are validated via a static fire test.

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A Nano-Satellite Swarm refers to a mission concept in which several to hundreds of low-performance nano-satellites are deployed in close relative proximity and perform coarse position control. In this paper, we propose a decentralized control method for autonomous formation of nano-satellites using the flocking algorithm. The Hill-Clohessy-Wiltshire (HCW) equation is used as the subject of this paper, and multiple nano-satellites are assembled to a target satellite in an autonomous decentralized manner under a randomly arranged initial state to form a lattice state known as α-lattice. By placing the nano-satellites on an orbit plane that can draw a periodic orbit called the General Circular Orbit (GCO), we aim to form an aggregated swarm state (α-lattice) without further control input. The required control effort and dynamic behavior during each phase are analyzed through numerical simulations.

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