JOURNAL OF RADAR
Year:2016 | Volume:4 | Issue:1 (SERIAL NO. 11)|Papers Count:6

Estimating direction of arrival (DOA) is more complicated when unknown non-coherent sources contain coherent signals or when sources are coherent. Recently, a new method based on uniform linear array (ULA) has been proposed that first determines the number of non-coherent sources and then estimates the DOA of coherent signals in each group. ULA is more applicable for DOA estimation but for estimating DOAs close to the array endfire, this configuration does not perform well or signals may be missed. Cross array (CA) is a suggestion to solve this problem but it offers a lower performance for middle angles and introduces more computational complexity. As the main goal of this investigation, using the proposed threshold-based JADEMUSIC algorithm, a new method is proposed which divides angles in two parts. For the angles which are in the range of [-60o, 60 o], horizontal elements of CA and for endfire angles and the angles which are in the range of [-90 o, -60 o] and [60 o, 90 o], vertical elements of CA are considered. Simulation results demonstrate that the new proposed scenario offers a higher performance for DOA estimation of narrowband signals with respect to ULA and CA configurations. Also, its computational load is the same as the case that uses ULA.

In this paper, a ground early warning receiver is introduced and explained for the reception and monitoring of signals from a space-borne synthetic aperture radar. This receiver can be used for various electronic warfare applications and implemented in two sectors of time parameter detector and frequency parameter detector. It can measure the signal power, bandwidth, central frequency, pulse width, pulse repetition frequency, antenna pattern shape, and imaging duration time from the received signal. In section of frequency parameter detector, the spectrum analyzer is used. Based on this receiver, a new method is invented for recognizing LFM signal from other pulse compression methods. Also, in this paper, a technique is demonstrated for identifying SAR signals from other signal sources and estimation imaging parameters. At the end of this report, several cases of success in receiving signals from COSMO-SkyMed and FIA-Radar are listed and some of the obtained parameters from signals are compared with the references. Also, features of space-borne SAR signals are described. in which bandwidth, pulse repetition frequency, imaging duration time, and power density are investigated using analytical relations.

A fast and accurate synthetic aperture radar raw data generator of moving targets has high importance, especially in the applications of the ground moving target indication. In this paper, by the hybrid time-frequency domain, a fast algorithm has been proposed for strip mode SAR raw data generation of moving targets. Using this simulator, in different conditions in terms of target motion speed, acceleration and direction, radar raw data has been generated and its final image has been extracted by Range-Doppler Algorithm. Then, the obtained images have been studied using the formula that have been extracted for predicting the effects of target motion parameters in the SAR images. The results show that the proposed simulator has a better performance in terms of speed than other existing simulators.

In this research, a framework is presented for the unsupervised change detection using Multitemporal SAR images based on integration of Clustering and Level Set Methods. Spatial correlation between pixels is considered by using contextual information. Furthermore, in the proposed method integration of Gustafson-Kessel clustering techniques (GKC) and Level Set Methods are used for change detection. Using clustering techniques has caused production of the initial curve for LSM with a minimum convergence time and, as a result, use of LSM Leads to increasing the accuracy of change map using the iterative process. In order to evaluate the performance of the proposed method, this method is compared with some other existing stateof-the-art methods. The results show that the total error rate of the proposed method has been reduced compared to these methods. Results show the high capability of the proposed method in the unsupervised change detection of multi-temporal satellite SAR images.