اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA Novel Scheme of Digital Instantaneous Automatic Gain Control (DIAGC) for Pulse Radars
79
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Several schemes for gain control are used for preventing saturation of receiver, and overloading of data processor, tracker or display in pulse radars. The use of digital processing techniques open the door to a variety of digital automatic gain control schemes for analyzing digitized return signals and controlling receiver gain only at saturating clutter zones without affecting the detection at other zones. In this paper, we present a novel scheme of Digital Instantaneous Automatic Gain Control (DIAGC) which is based on storing digitally the dwell based clutter returns and deriving the gain control. The returns corresponding to the first two PRTs in a dwell are used to analyze the presence of saturating clutter zones and the depth of saturation. Third PRT onwards proper gain control is applied at the IF stage to prevent saturation of the following stages. FPGA based scheme is used for digital data processing, storing, threshold calculation and gain control generation. The effect of DIAGC on pulse compression is also addressed in this paper.
قيم البحث
اقرأ أيضاً
Automatic modulation classification enables intelligent communications and it is of crucial importance in todays and future wireless communication networks. Although many automatic modulation classification schemes have been proposed, they cannot tac
kle the intra-class diversity problem caused by the dynamic changes of the wireless communication environment. In order to overcome this problem, inspired by face recognition, a novel automatic modulation classification scheme is proposed by using the multi-scale network in this paper. Moreover, a novel loss function that combines the center loss and the cross entropy loss is exploited to learn both discriminative and separable features in order to further improve the classification performance. Extensive simulation results demonstrate that our proposed automatic modulation classification scheme can achieve better performance than the benchmark schemes in terms of the classification accuracy. The influence of the network parameters and the loss function with the two-stage training strategy on the classification accuracy of our proposed scheme are investigated.
Digital maps will revolutionize our experience of perceiving and navigating indoor environments. While today we rely only on the representation of the outdoors, the mapping of indoors is mainly a part of the traditional SLAM problem where robots disc
over the surrounding and perform self-localization. Nonetheless, robot deployment prevents from a large diffusion and fast mapping of indoors and, further, they are usually equipped with laser and vision technology that fail in scarce visibility conditions. To this end, a possible solution is to turn future personal devices into personal radars as a milestone towards the automatic generation of indoor maps using massive array technology at millimeter-waves, already in place for communications. In this application-oriented paper, we will describe the main achievements attained so far to develop the personal radar concept, using ad-hoc collected experimental data, and by discussing possible future directions of investigation.
Long Range (LoRa) has become one of the most popular Low Power Wide Area (LPWA) technologies, which provides a desirable trade-off among communication range, battery life, and deployment cost. In LoRa networks, several transmission parameters can be
allocated to ensure efficient and reliable communication. For example, the configuration of the spreading factor allows tuning the data rate and the transmission distance. However, how to dynamically adjust the setting that minimizes the collision probability while meeting the required communication performance is an open challenge. This paper proposes a novel Data Rate and Channel Control (DRCC) scheme for LoRa networks so as to improve wireless resource utilization and support a massive number of LoRa nodes. The scheme estimates channel conditions based on the short-term Data Extraction Rate (DER), and opportunistically adjusts the spreading factor to adapt the variation of channel conditions. Furthermore, the channel control is carried out to balance the link load of all available channels with the global information of the channel usage, which is able to lower the access collisions under dense deployments. Our experiments demonstrate that the proposed DRCC performs well on improving the reliability and capacity compared with other spreading factor allocation schemes in dense deployment scenarios.
This article develops the multiple-input multiple-output (MIMO) technology for weather radar sensing. There are ample advantages of MIMO that have been highlighted that can improve the spatial resolution of the observations and also the accuracy of t
he radar variables. These concepts have been introduced here pertaining to weather radar observations with supporting simulations demonstrating improvements to existing phased array technology. Already MIMO is being used in a big way for hard target detection and tracking and also in the automotive radar industry and it offers similar improvements for weather radar observations. Some of the benefits are discussed here with a phased array platform in mind which offers quadrant outputs.
Controlling the quadrature measured by a homodyne detector is a universal task in continuous-variable quantum optics. However, deriving an error signal that is linear across theentire range of quadrature angles remains an open experimental problem. H
ere we propose a scheme to produce such an error signal through the use of a universally tunable modulator.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
