فهرست مطالب morteza kazerooni

In this paper, the calculation of the dimensions of the area illuminated by the antenna (antenna footprint) of an Airborne Ground Penetrating Radar (airborne GPR) has been investigated on the ground's surface and subsurface. In the topic of detecting buried targets by airborne GPR radars, knowing the area illuminated by the radar antenna is very important. By having the dimensions of the illuminated area, we can cell the search area according to it and excite these cells with appropriate power and at a certain time. The advantages of celling according to the antenna footprint are managing the transmitted power and reducing the search time. In this paper, two methods are provided to simulate the detection of buried targets in CST software. In the first method, a horn antenna is used as a radiation element in the structure itself, but in the second method, the antenna is simulated separately and its parameters are used to calculate the antenna footprint. In the first method, the meshing is very large due to the distance between the antenna and the ground's surface, which increases the simulation time, but in the second method, due to the removal of this distance and the use of the antenna footprint as a radiation element, the meshing And the simulation time is greatly reduced.

In this article, the effective parameters in detecting and identifying buried targets have been investigated. These parameters affect the electrical permittivity of the soil and can determine the penetration depth of the waves in the soil. Knowing the type of soil and the electrical conductivity of the soil, as well as the penetration depth of electromagnetic waves in it, can help us choose the appropriate frequency, antenna type, and transmission power, and in general, optimize the radar parameters. This can prevent resource waste and reduce search time to an acceptable level, and increase the efficiency of the radar system. The effect of physical and environmental parameters on 7 soil samples has been investigated, and the electrical permittivity coefficient and the depth of wave penetration in them have been calculated. In the next stage of simulation, loamy clay & sand soil is used as a reference soil and changes in compression, temperature, and humidity are applied to it, and according to each stage, the electrical permittivity coefficient and the penetration depth of wave are calculated. In the final stage of the simulation, the detection process of a buried metal target has been simulated in CST software according to the available detection depth in the previous stages. The biggest effect on electrical permittivity is related to changes in soil moisture. The maximum penetration depth of waves in dry soil with a frequency of 100 MHz is about 23 meters, and with the increase in soil moisture, the penetration depth of waves decreases to 1 meter.

Sea target detection in the HSP-FLSAR images has not been addressed so far in the literature. In this paper we carry out a comparative evaluation of existing SAR target detection algorithms in the case of monostatic HSP-FLSAR range Doppler images assuming a platform diving trajectory. To do so, various CFAR methods, including CA-CFAR, SOCA-CFAR, GOCA-CFAR, OS-CFAR, VIE-CFAR, and G0 distribution CFAR algorithms, are used to detect a set of point scatterers in simulated images. The performance of methods is compared based on receiver operating characteristic curves. Simulation results show that OS-CFAR has the best probability of detection for a fixed probability of false alarm. This paper can be a starting point to find better target detection methods in HSP-FLSAR images.

The main goal of this article is to investigate the parameters and components influencing the detection of a buried target by a static airborne radar platform by means of loop propagation modeling. In this modeling, the dimensions of the antenna coverage range on the surface and subsurface have been calculated by taking into account all the effective parameters, which allows us to use the radiative transfer theory and determine the amount of input current in each environment, the scattered and absorbed power obtained in the medium. One of the important points in the applications of this type of airborne radars is the proper selection of the central frequency and the frequency bandwidth required for better detection. In this paper, how to choose the parameters of radar design and compromise between having penetration depth and having the resolution are properly presented using delimited diagrams that can be placed as a predefined table in radar memory. Also, with the arrangement of several scenarios, the amount of return signal from the buried target has been measured and verified in CST and GPR_Sim software, and through equations, the depth of its placement has been revealed with an acceptable accuracy of less than 2%.

The main purpose of this article is to design and simulate an algorithm for the buried target from InSAR, and the purpose of this study is to start with the construction and analysis of the subsidence rate of the subway tunnel in the construction of Isfahan city.The main connections of InSAR for the construction and monitoring of subsidence of such goals are in determining the measuring time and reducing the correlation due to the change of the reflective characteristics of the geographical objects over time, which leads to the reduction of the interference coherence.In the design of this algorithm, an attempt has been made to increase the degree of coherence between the interference views by using the interferometer radar time series processing and the selection of widespread stable scatterers, as well as the optimal and continuous graphic design between the images under processing, which causes the stability of the phase of the distributed targets. Also, in order to reduce the amount of noise in the interference of views, in the stage before phase unwrapping, by applying a filter and suitable parameters to increase the signal to noise, in which the average coherence in the interference of the created views is 9% compared to other filters. It is closer to the number 1, which is the highest level of coherence, and in the end, in order to increase the accuracy and not to remove the regions with relatively low coherence, we will implement the optimal fuzzy unwrapping algorithm, which measures the average absolute value of the relative error in phase unwrapping by 12%. Finally it is clear that the subsidence of the target under study is different from the subsidence caused by natural causes such as underground water or drought and has a recognizable subsidence pattern.

The microwave chamber disturbance method (CDM) is a commonly used procedure for determining the electromagnetic properties of materials in the microwave frequency range. This method is based on the change in the resonance frequency and the quality coefficient of a measurement chamber due to the penetration of the sample at the location of the maximum electric or magnetic field, depending on the nature of the parameter under study. The main limitation of the CDM is the requirement that the sample size must be small so as not to have a negligible effect on the geometry of the fields inside the chamber. In this paper, we propose an enhanced CDM for accurate measurement of dielectric constant and magnetic permeability of materials with very low error rates. The chamber consists of a rectangular waveguide with a cap that fits the location of the sample. This arrangement provides a suitable measuring device that minimizes the measuring errors, including the uncertainty in the perforated plate and use of liquid adhesive for sample-waveguide attachment. To validate the accuracy of the proposed method, the predicted values of dielectric constant and magnetic permeability of several sample materials are compared with their actual values and the error rate of this proposed method has finally reached less than 1.5%

The process of development and expansion of advanced industries reveals the need to implement more and more predictive methods and mechanisms in readiness to deal with possible failures. With complexities inherent in systems, having a proper and all-embracing model of the entirety of a system is not readily possible. Design structure matrices (DSMs) are regarded as great (a great) help in communicating, comparing, and integrating partial system models. Given that there are numerous relationships among subsystems in complex systems, it is expected that interactive failures occur giving rise to diverse problems as well as gradual or abrupt failures in the system. Correlational dependent (Correlational-dependent) failures, commonly known as interactive failures, most frequently occur in mechanical systems. In this study, we have exploited DSM for identifying interactive failures and the relationships existing among different components in complex systems. The latter matrix is generally used in industries for observing the strengths of existing relationships among interacting elements. From another perspective, by analyzing the relationships among elements and identifying coils and curls, it is possible to investigate the existing nodes in loops. Implementing this procedure leads to identifying critical components and interactive failures, eventually bringing about enhanced reliability in the system. The present paper, while considering prevailing methods adopted in previous studies for selecting critical parts and subsystems, proposes a new method for selecting critical parts so as (delete so as) to increase the reliability rates. The method set forth is derived from the Markov chain model in addition to employing mathematical methods in matrices.

Design, simulation and optimal selection of cosine-linear frequency modulation waveform (CNLFM) based on correlated ambiguity function (AF) method for the purpose of Synthetic Aperture Radar (SAR) is done in this article. The selected optimum CNLFM waveform in contribution with other waveforms are applied directly into a SAR image formation algorithm (IFA) and their quality effects performance in comparison to each other is analyzed. The quality performance analysis includes both the qualitative AF diagrams and the objective image quality metrics assessments. Then, by changing the SAR system parameters based on the proposed CNLFM waveform, other quality metrics are also derived. The simulation results verifies the robustness of the proposed CNLFM waveform implementation as a suitable NLFM alternative for LFM waveform.

Phase shifters are devices, in which the phase of an electromagnetic wave of a given frequency can be shifted when propagating through a transmission line. In many fields of electronics, it is often necessary to change the phase of signals. RF and microwave phase shifters have many applications in various equipments such as phase discriminators, beam forming networks, power dividers, linearization of power amplifiers, and phase array antennas. Phase shifters are divided into two group diode and ferrite. In this paper a ferrite phase shifter is investigated. Ferrite phase shifters are two-port devices that may be either analog or digital with either reciprocal or nonreciprocal characteristics. In previous works, magnetic flux densityB-magnetic field intensity curve or B-H Hcurve of a ferrite core is obtained. In this paper, phase shift-current curve or Ø-I curve of a reciprocal analog ferrite phase shifter is simulated and the effect of various parameters tolerances, such as permeability, permittivity, frequency and length of ferrite rod on the Ø-I curve is shown.

Wireless sensor networks are significant technologies nowadays which provide opportunities for several military and industrial fields. One of the most crucial of these applications is field and border monitoring. Detection and recognition of an intruder is performed based on sensor measurements from environment. Implementation of suitable pattern-recognition algorithms is necessary to process these data. This paper presents a comparison between performances of the most commonly used algorithms in this field from different points of view. Also a new algorithm for weighted decision fusion is introduced. It will be shown that with help of this algorithm, the result will become more accurate. The accuracy of this algorithm is about 11 percent better than common decision fusion algorithms.