عنوان مقاله [English]
Positioning the car in the parking lot is an important factor to make the parking lots smarter, as a result of which it is possible to steer the car, which will be a factor to increase the quality of service in the parking lot. Due to the closed environment of the parking lot, locating objects in it, including locating objects in indoor environments. The use of radio waves and related methods to locate indoors is one of the solutions presented in this field. In some other methods in this field, the location of the object in the indoor space is calculated only by using the equipment available in the environment (similar to location radars). Disadvantages of both methods include the need for additional equipment at high prices, extreme sensitivity to environmental conditions and existing noise. In this research, an attempt has been made to perform the location process by using monopole antennas and scattering matrix. For this purpose, first, the parking environment is simulated with a plate containing several monopole antennas, and using finite element-based software, the scatter matrix is obtained for the absence and presence of the object in different environmental conditions that have been simulated. After calculating the scattering matrices, the required data are selected and each of these values is assigned to an object position using a neural network. In the next phase, in exchange for placing the object in the new position, the corresponding scattering matrix is obtained and the object is calculated by comparing it with the information collected in the previous step. This process is similar to the fingerprint algorithm, except that instead of using the values of signal strength, the matrix is scattered. The advantages of this method include no need to calibrate and accurately measure the position of the antennas, scalability and provide a new solution to reduce costs and increase the accuracy of calculating the position of the object.