JOURNAL OF RADAR
Year:2015 | Volume:3 | Issue:3 (SERIAL NO. 9)|Papers Count:6

In this paper, we examine target detection in FM-based passive bistatic radars (FBPBRs) in the presence of interference signals received in the reference channel of these systems. To do so, we propose a new signal conditioning algorithm to remove interference signals form the reference channel. Simulation results show that the proposed signal conditioning algorithm outperform the one presented in [1]. In addition to this, we evaluate the detection performance of cell averaging (CA) detector in the surveillance channel of an FBPBR in the presence of interference signals with exponential power spectral density. In this case, simulation results show that the proposed detection algorithm provides at least 11dB improvement when compared with its counterpart.

This paper describes the design of a 2x2 micro strip patch antenna array in the frequency of 9.5GHz for radar applications, using substrate integrated waveguide, SIW, for feeding network. The micro strip patches are aperture-coupled with the feeding network of SIW. The feeding network consisting of a perpendicular coax-to-SIW transition and two Y-junction power dividers. The antenna is simulated in full wave software of CST and the prototype is fabricated. The measurement results good agreement with the simulation results. a fabricated prototype has a gain of 11.6dB and a side lobe level below -14.5dB in the E-plane and -18dB in the H-plane.

In synthetic aperture radar (SAR) imagery, ship-sea contrast can be significantly improved when the polarimetric information is used, compared with information from a single channel SAR. The constant false alarm rate (CFAR) detection algorithm based on the alpha-stable (AS) distribution model is a descent method for ship detection in sea. The most important step in this method is the parameter estimation of the AS probability density function for which the method of log-cumulants (MoLC) parameter estimation is proposed and utilized in this study. Evaluation results of the proposed method on two L- and C-band polarimetric SAR (PolSAR) datasets which are acquired by AIRSAR and RADARSAT-2 sensors confirm the accuracy of the method. Experimental results show that the best results of detection maps are achieved when the polarimetric span and entropy data are used where a high detection accuracy in the latter cases are along with a low number of false alarms.

Study on PolSAR target detection essentially requires the scattering information and polarimetric statistical data. Theoretical analysis shows that some terms of the second order scattering matrices such as coherence and covariance matrix clearly show the differences between nonsymmetrical man-made objects and natural clatters which being reflection symmetric. Using the model derived from these terms the automatic target detection and extraction with a constant false alarm rate established. In this model, various capacity of manmade and sea targets in symmetrical reflection studied and polarimetric SAR data acquired in L- and C-band have been used to test the proposed methodology showing to be an effective and efficient method to observe metallic targets at homogeneous and non-homogeneous areas of sea, such as detection of ships, oil rigs, building and other structures.

The polarimetric entropy and the alpha angle are two important parameters for analyzing polarimetric synthetic aperture radar data. They demonstrate the degree of randomness in the polarization of the received signal and scattering mechanism of scatterers respectively. Recently, there has been an increasing interest in compact polarimetry due to its advantages in comparison with full polarimetry. Because the information of compact polarimetry mode is less than full polarimetry mode, it is important to reconstruct full polarimetric information from compact data as better as possible. In this article based on the correlations between alpha and entropy parameters in the compact and full polarimetry modes, a novel method is presented in order to reconstruct Cloude-Pottier entropy and a-angle from compact polarimetric data which has reduced computational time and volume in comparison with the previous approach, also the coefficient of determination for entropy and alpha has been increased 7.74% and 0.6% and RMS error has been decreased 4% and 0.5% respectively.

In this paper a new method is presented which minimizes the destructive effects of measurement noise belonging to delays between receiver sites in accuracy of locating targets. For this purpose the geolocation equations are re-written by considering measurement error, therefore a cost function is introduced subject to position of sites, time difference of arrival of signals and measurement noise. By optimizing this function an estimation of the measurement error is obtained and a considerable improvement may be performed in locating targets by correcting existing delays by applying the above estimated values. Performance of the proposed method is evaluated in two different scenarios, corresponding to real conditions. As a result an accuracy improvement of about 1100 meters is achieved for target detection, in both scenarios compared to existing positioning method which doesn’t contain the proposed compensation.