Preliminary Development of a Hydrogen Peroxide Thruster

Green propellants used for satellite-level propulsion system become attractive in recent years because the non-toxicity and lower requirements of safety protection. One of the green propellants, high-concentration hydrogen peroxide H2O2 solution (≥70% w/w, weight concentration percentage), often known as high-test peroxide (HTP), is considered because it is ITAR-free, easy to manufacture and the operating temperature is lower than traditional monopropellant propulsion. To establish satellite propulsion technology, the National Space Organization (NSPO) in Taiwan has initialized a long-term cooperation project with the National Cheng Kung University to develop compatible tank and thruster. An experimental propulsion payload has been allocated for the future self-reliant satellite to perform orbit transfer and maintenance operations. In the present research, an 1-Newton thruster prototype is designed and the thrusting force is measured by a pendulum-type platform. The preliminary hot-firing test at ambient environment showed the generated thrust and the specific impulse are about 0.7 Newton and 102 seconds, respectively.

Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.