JOURNAL OF RADAR
Year:2020 | Volume:8 | Issue:1|Papers Count:13

The main challenge for airborne radars in discovering ground targets is the removal of Clutter and Jammer. The adaptive space-time processing method is the newest method of processing against these signals. The space-time processor creates a two-dimensional filter, which sets zero (null) angular and Doppler frequencies where Jammer and clutter are signaled. In computing the optimal weight vector for this filter, the covariance matrix of the interference signals is required. In practice, the covariance matrix of the signal is not interfering and should be estimated. The estimation of covariance matrix is based on recursive signals and according to other target cells other than the target cell (secondary data). The main problem in estimating this matrix is the limitation of the number of secondary data that is homogeneous and reliable. Different processing methods have been devised to increase convergence and reduce computational volume. The use of de finite filters facilitates the convergence and faster updating of the weighted vector and eliminates the processes caused by the inversion of the covariance matrix. In this paper, the recursive method has several parallel processing branches associated with weight reduction and drop-down matrix updating approach which, in comparison with previous recursive methods, results in improved performance by having a limited number of secondary data.

In this paper, the problem of elliptic target localization in distributed multiple-input multiple-output (MIMO) radars is investigated. The goal of elliptic localization is to estimate the target position from a set of noisy bistatic delay measurements. Since the maximum likelihood (ML) problem associated with elliptic localization is nonconvex, iterative methods can be trapped in local minimums, leading to inaccurate location estimation. To solve this problem, a number of (almost closed-form) estimators are proposed, which can locate the target without convergence concern. The proposed methods are efficient, achieving Cramer-Rao lower bound (CRLB) up to relatively high noise levels. These methods are of superior localization accuracy in comparison with the state-of-the-art methods. Furtheremore, according to the closed-form and algebraic nature of the proposed methods, they have very low computational complexity, which is similar to other existing closed-form methods in the literature. It should be noted that the ideas presented in this paper can be considered as a baseline for future research studies in the area of localization in radar systems.

This paper designs the transmit covariance matrix in the correlated MIMO radar. Covariance matrix of the transmit signal directly affects the performance of radar, including the received beam pattern and the signal-to-interference plus noise ratio (SINR), and consequently the probability of detection. By designing the structure of the covariance matrix, the appropriate transmit waveform can also be obtained. Among the challenges in designing a covariance matrix is the high side lobe levels (SLLs) in the received beam pattern, as well as the need to use several high-cost waveform generators in multi-antenna systems. The proposed structure for the covariance matrix in this paper has much lower SLLs than other existing designs. It has not only a better detection probability than other methods, but also has a simpler transmitter. It is shown that the proposed design can be implemented with a very simple BPSK waveform, so unlike other methods, there is no need to use multiple waveform generators in the transmitter. This will significantly reduce the cost of the transmitter. Simulation results demonstrate that the receive beampattern of the proposed scheme has much lower SLLs and for the constant false alarm rate, it has higher detection probability in comparison with correlated MIMO radar.

One of the important issues in the aviation industry is the Stealth of flying vehicles. One of the stealth methods is to reduce the radar cross section of the target body by means of plasma coating and plasma absorption properties. DBD plasma actuators are widely used in flow control; however, this experimental study was designed to assess their effect on the level of radar cross section on flat plate in the setting of different voltages and frequencies. Plasma placement was investigated in two defferent configurations. Results reveal that the number and distance of the plasma actuators as well as their arrangement can influence the radar cross section. The study could eventually achieved 43. 37% (~2/46 dB) reduction in radar cross section using DBD plasma actuator in frequency of 6 KHz and best arrangement.

Localization by the received signal Strength (RSS) measurement is inexpensive and has low computational complexity, thus extending the lifetime of the sensors in the wireless sensor network. The conventional propagation model for RSS has a log-normal distribution and since the probability density function is known, the best estimator for localization is Maximum Likelihood Estimator (MLE). The ML estimator is nonlinear and nonconvex and Gauss-Newton and convex optimization methods are presented in the papers. These methods impose a lot of complexity on the system and reduce the energy of the battery. In this paper, a two-step linear estimator is employed to solve the nonlinear ML estimator. In the first step, a new DRSS model is presented and nonlinear terms of ML cost function are replaced with linear variables. Also, in contrast to the estimators based on the conventional DRSS model, the performance of this estimator doesn't reduce by the random selection of the number 1 reference node. In the second step, the error of approximation of the first step is minimized, thus increasing the accuracy of the location estimation. Simulations show that in both the first and second steps, the accuracy is improved and the average error root error is reduced by up to 13% compared to the existing estimators.

In the recent decade, GaN HEMT power transistors have gained increasing popularity among radar power amplifier designers. To design a microwave power amplifier using a GaN HEMT transistor, we need a large-signal model for the transistor, which accurately characterizes its behaviour. The first step to implement large-signal modelling is to build small signal modelling. The small-signal model of a transistor can be apportioned into two extrinsic and intrinsic parts. For the extraction of intrinsic elements, the extrinsic elements should be extracted at first. In this paper, The Parasitic capacitors and inductors of a typical transistor are calculated directly and without the need for optimization at low frequencies using measurement results in different operating conditions. And then with a few matrix conversions and direct relationships, the parasitic resistors of the transistor at a bias point belong to the active region (no need for gate-source voltage greater than zero) are calculated. The improved method is verified by comparing the simulated small-signal S-parameter with the measured data up to 10GHz. Results indicate that the error is less than 4% in the operating frequency band of the transistor. In comparison with counterpart optimization methods, this method takes less time and is less complicated.

Radar is an electromagnetic device used to detect and determine the position of targets. The most basic task of radar is to extract information about the target by measuring the electromagnetic field characteristics of the return waves from the target. The radar environment of each country is one of the security and strategic areas of each country. Maintaining the security of this environment and identifying its goals can be one of the important requirements. Challenges and problems such as inaccuracy and inaccuracy of detection and high error are raised in the detection of radar targets. Various methods have been proposed so far, such as techniques based on target natural intensification frequencies, reversible signal polarization, machine learning methods, etc., to detect radar targets. Despite the many uses of these methods, they have not yet been able to meet the challenges of radar. Therefore, in this paper, we have identified radar targets using the GMDH Deep Learning Algorithm. By simulating the proposed method and comparing it with other methods such as RIN, SAE, SCAE, SDAE, CNN, LSVM, K-SVD, the average has improved by 5%.

Moving target indication (MTI) filters are generally considered as the primary approach to remove echo caused by fixed unwanted targets as well as clutter, in real-world radar systems. The MTI filter is set up as a linear combination of the echoes received from the range cell under test, when the inter-pulse periods (IPPs) are staggered. Hence, the MTI filter is mainly characterized with the coefficients and the IPPs. The MTI filter design problem is to optimize both these parameters to maximize both the blind speed and the clutter rejection, while providing the required signal gain. In this paper, to calculate the coefficients, the deviation of the designed filter from the ideal one in pass-band is optimized using the least squares criterion. The coefficient optimization is done under the constraint to induce nulls at limited number of frequency spots in the clutter rejection band to increase clutter rejection. As to the IPPs, a random IPP search is done to maximize the minimum SCR in the pass-band. At the analysis stage, the performance of the proposed method is compared with the other existing methods, based on two criteria: Improvement Factor (IF) and the minimum SCR gain in the pass-band. Eventually, it is shown that the proposed method has better results.

In the present work the scattering of EHF radio waves from a plasma elliptical hybrid antenna is investigated by the Finite Element-Boundary Integral (FE-BI) method. This antenna is made of a dielectric elliptical column covered by a plasma layer as a dispersive medium. The plasma cover has elliptical cross section and has been magnetized by an external constant magnetic field along axis of the antenna. Different geometric configurations of the antenna are examined by changing the position of the dielectric column relative to the plasma layer, so that their large diameters vary from 0 to 90 degrees relative to each other. As will be seen, due to anisotropy of geometric configuration and permittivity tensor of the plasma layer, the angle of incidence and geometrical parameters are very effective on the antenna response. Finally, numerical analysis shows how one can control profiles of the electromagnetic fields and scattering cross section of the antenna by varying the external magnetic field intensity and polarization of the incident wave. The presence of various variables in this antenna makes it significantly flexible and tunable, that is especially important in the cloaking processes.

Determining the third dimension of the underwater targets, by the sonar system, can play an important role in three dimensional imaging and target recognition. In this paper, by applying the inverse synthetic aperture sonar and using the seabed virtual source and a second sensor, the third dimension of the targets is obtained. For obtaining the third dimension, we use the distance between the scatterer and its two main corresponding artifacts in the two dimensional image. In the case of having two sonar systems, with both the transmitting and receiving roles, the third dimension resolution is increased obviously, compared to the monostatic case explained in our previous paper. In addition, because of having these two sensors, more target scatterers will be in the view of sensors. By using the information obtained in this way, it is possible to achieve more accuracy in calculating the third dimension and create a three-dimensional image of the target. Because of the importance of the underwater monitoring, using the proposed scenario, we can use this system for more accurate identification of the targets to counter the threats and for the defence applications.

In this paper we present a one-dimensional monopulse antenna in groove gap waveguide (GGW) technology. A riblet coupler with a 90 degree delay line is designed to achieve proper sum and difference performances of the monopulse comparator. The outputs of designed 180 degree hybrid are connected to 4 way power dividers in order to feed the radiating elements. A 1×8 array of slots is used as the radiating section of the proposed antenna. A sample antenna is designed and simulated for operation at Ku band. Simulation results show that the return loss is more than 10 dB around 14GHz center frequency and the proper sum and difference performances.

Design and simulation of high directive waveguide directional couplers based on supershapes are presented, in the present paper. In order to obtain high directivity, circular holes in a conventional coupler are equivalently substituted with supershape holes. In the frequency range from 8 to 12 GHz, the coupling values of two proposed couplers are 19± 1 dB and 23± 2 dB and the directivities are better than 20 dB. The simulation results show that almost 20 dB improvement in the directivity can be achieved as compared to a conventional coupler. The results are valuable for the design and development of broadband high directive waveguide couplers.