Abstract: One of the defects of stepped frequency radar systems
is their sensitivity to target motion. In such systems, target motion
causes range cell shift, false peaks, Signal to Noise Ratio (SNR)
reduction and range profile spreading because of power spectrum
interference of each range cell in adjacent range cells which induces
distortion in High Resolution Range Profile (HRRP) and disrupt target
recognition process. Thus Target Motion Parameters (TMPs) effects
compensation should be employed. In this paper, such a method
for estimating TMPs (velocity and acceleration) and consequently
eliminating or suppressing the unwanted effects on HRRP based on
entropy minimization has been proposed. This method is carried out
in two major steps: in the first step, a discrete search method has
been utilized over the whole acceleration-velocity lattice network, in a
specific interval seeking to find a less-accurate minimum point of the
entropy function. Then in the second step, a 1-D search over velocity
is done in locus of the minimum for several constant acceleration
lines, in order to enhance the accuracy of the minimum point found
in the first step. The provided simulation results demonstrate the
effectiveness of the proposed method.
Abstract: The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.