Research On The Micro Intelligent Magnetic Heading System

Magnetic heading system (Mi-IS) or electric magnetic compass is an essential device used to measure the heading of ships, aircraft and land vehicles. With the development of modern unmanned aerial vehicle (UAV) , digital MHS becomes an important measuring device on UAV. But the larger size and higher power consumption of existing digital Mi-IS influences the performance of UAV, especially used in the micro UAV. The higher cost of the deviation compensation and error correction is another problem of existing digital MHS. This thesis studies micro intelligent MHS to solve these problems. Fluxgate is suitable sensor for MHS. We analyzed recent studies on micro-fluxgate and finded out that the power consumption of most micro-fluxgate was relative high. One of the focal point of the dissertation is to study low power fluxgate. We put forward a new kind of fluxgate structure, witch has different core cross section located in the excitation and pick-up coils, to lower the excitation current simply and effectively, and find out the relation between the ratio of the two area and the excitation current. We design a 16-bit microprocessor unit (MPV) with our own copyright for the micro intelligent MHS. The MPU is compatible with Intel microprocessor at instruction level. We design a single internal bus structure to simple the data pass, use optimized micro program to control the execution of all instruction, and design an instruction decoder controlled by an eight梥tate state machine to solve the contradiction between the complex instruction set and internal regulation design. The dissertation discusses a compensation method witch need to known exact values of the heading, pitch and roll angle of UAV in experiment. Such method is so complex that need a day?s work of a team of specialist, though we put forward a method to find the mistake in the experiment data. The dissertation put forward two kinds of automatic compensation methods witch made the compensation experiment can be done automatically in the flying test of UAV. When UAV flying in horizontal, we described the formation of errors as changes from circle to ellipse in geometry, called ellipse hypothesis. Thereverse process from e1l ipse to circle can be used to compensate deviation andcorrect error. The data needed to determine the ellipse is samp1ed by MPUautomatica11y. When UAV f1ying in arbitrary attitude, we can use el1ipsoidhypothesis. But the UAV's ideal attitudes for data sampling are only three,f1ying in horizonta1, 1eft dec1ine and right dec1ine. Data samp1ed at theseatt itudes can not determine an el1 ipsoid perfect1y, so we put forward an el l ipsemethod to solve the problem. This method simplifies the deviation compensationand error correction experiment that only need UAV circ1es left one time andcircles right one time in its flying test.In order to test and verify above theories and methods, a prototype microintelligent MHS is developed. A virtua1 instrument used for the prototypedevice is also developed. Experiment reSults show that the prototype deviceworks well and the two kinds of automatic compensation methods are a11effect ive l y.