In this work, a comparative study on the ballistic behaviour of friction stir processed AL6061 targets had been made. Base Metal AL6061 (BM) plates with 25 mm thickness were friction stir processed by adding Multi Walled Carbon Nano Tubes (MWCNT) and Graphene (G), producing AL6061-MWCNT and AL6061-G surface composites. Optical microscopy and microhardness test on BM, AL6061-MWCNT and AL6061-G samples were performed as per the standard procedure. It was noticed that uniform dispersion of ceramic particles and refined grains were obtained for the friction stir processed surface composites. From the microhardness test, it was perceived that friction stir processing had induced strengthening of surface composites, hence increasing the microhardness of AL6061-MWCNT and AL6061-G by ~60.3% and ~73.6% respectively. Also, ballistic experiments were conducted at 680±10 m/s by impacting Ø7.62×51 mm projectiles. AL6063 backing plates were placed to compare the ballistic behaviours AL6061-MWCNT and AL6061-G targets by depth of penetration. It was noted that the depth of penetration of AL6061-MWCNT and AL6061-G targets were 37.81% and 65.84% lesser than the BM target. Further, from the results of Post ballistic microscopy it was observed that the microstructure near and away from the penetration channel edge looks unchanged in BM target. However, the AL6061-MWCNT and AL6061-G targets showed considerable change in their morphology, by forming Adiabatic Shear Bands.

A navigation complex of an unmanned flight vehicle of small class is considered. Increasing the accuracy of navigation definitions is done with the help of a nonlinear Kalman filter in the implementation of the algorithm on board an aircraft in the face of severe limitations on the performance of the special calculator. The accuracy of the assessment depends on the available reliable information on the model of the process under study, which has a high degree of uncertainty. To carry out high-precision correction of the navigation complex, an adaptive non-linear Kalman filter with parametric identification was developed. The model of errors of the inertial navigation system is considered in the navigation complex, which is used in the algorithmic support. The procedure for identifying the parameters of a non-linear model represented by the SDC method in a scalar form is used. The developed adaptive non-linear Kalman filter is compact and easy to implement on board an aircraft.