毕业设计开题报告_吕东旭_简易短距离无线图传系统的设计(定稿)
无线数据传输系统设计开题报告
无线数据传输系统设计开题报告
吉林化工学院信息与控制工程学院
毕业设计开题报告
基于单片机的无线数据传输系统设计
Design of the Wireless Data Transmission System Based on Chip
Microcomputer
学生学号：11510225
学生姓名：高海昌
专业班级：自动1102
指导教师：李楠
职称：讲师
起止日期：2015.03.22～2015.04.03
吉林化工学院
Jilin Institute of Chemical Technology
说明：
1. 本报告前6项内容由承担毕业论文(设计)课题任务的学生独立撰写；
2. 本报告必须在第八学期开学三周内交指导教师审阅并提出修改意见；
3. 学生须在小组内进行报告，并讨论；
4. 本报告作为指导教师、专业系或毕业论文(设计)指导小组审查学生能否承担该毕业设计(论文)
课题和是否按时完成进度的检查依据，并接受学校和教学院的抽查。
无线大屏信息发布系统的设计与实现开题报告
无线led显示屏是一种全新的信息媒体，一经面世，便被广泛的社会媒体所接受其流动信息和联网信息发布的特点更为广告界所推崇，成为一种全新的的广告媒体。
无线led显示屏信息发布系统特点：
1. 组网规模大/传统led显示屏的内容有电脑通过串口数据线发送，显示屏在数量规模上受到限制，无线led显示屏发布系统通过DTU来发布信息，采用[3]TCP/IP网络传输协议，终端联网数量不受限制。
2. 实时信息发布。传统led显示屏只能固定的显示所控制器内存储的信息，如需发布新的信息无线led显示屏可以随时接受信息中心下发的信息。
3. 不受距离限制，传统电子显示屏只能在短距离内使用，一般只有数十米，无线led显示屏在全国范围内，只要无线网络覆盖的地方都可以使用，不会距离和位置的限制。
4. 安装维护方便。由于不需要铺设光缆和通讯电缆，所以无线led显示屏的安装位置易于选择， 产品采用模块化设计，便于维护和检修。
无线 LED 显示屏信息发布系统应用领域：
作为一种新的信息发布载体，无线 LED 显示屏信息发布系统具有广阔的市场和用途，可广泛用于政府、商业、交通、餐饮、建筑、旅游、体育、运输等行业和部门。
小区楼院：将无线 LED 显示屏安装在小区、楼宇、院子入口处，作为小区信息公告牌，方便物业和居民发布物业通知、公益资讯、小区公告、气象信息、安全知识、交通提示、社区信息等，有助于社区信息的整合与传播，净化社区环境，提升社区形象;
以嵌入式系统为平台,依赖于无线网络进行数据传输,成本越来越低,通信更加可靠。在此基础上开发与之对应的一套完整的应用系统,用户可以在任何一台智能终端上通过特定的客户端对设备进行配置、管理、查看,因此具有重要的研究意义和应用价值。户外LED大屏信息发布系统作为一种全新的信息媒体,已被广泛的应用。
通信工程毕业论文开题报告-基于WIFI的无线传感器采集系统设计
长春理工大学毕业设计任务书题目名称：基于WIFI的无线传感器采集系统设计学生姓名：华丹阳起止日期：2016.3.3~2015.6.22指导教师签字系主任签字年月日II. RELATED WORKPrior work in optical wireless using visible light that use photodiode receivers or imaging receivers are either limited to short ranges or require complex processing at the receiver [17], [21], [22]. Though photo diodes can convert pulses at very high rates, they suffer from large interference and background light noise. This results in very low SNRs and thus short communication ranges. We showed analytically in [6], based on the visual MIMO concept, that a camera receiver outperforms photodiode receivers in terms of its channel capacity at medium to long ranges. Recently, a few sporadic projects have begun to investigate cameras as receivers, particularly for inter-vehicle communications [21] and traffic light to vehicle communications [8]. Their analytical results show that communication distances of about 100m with a BER10 6 are possible. Other work has investigated channel modeling [18] and multiplexing [7]. While earlier work has also used cameras to assist in steering of FSO transceivers [25], the visual MIMO approach differs by directly using cameras as receiver to design an adaptive visual MIMO system that uses multiplexing at short distances but still can achieve ranges of hundreds of meters in a diversity mode.Only a few projects till now have investigated MIMO techniques for optical wireless. For shorter range systems [15], [26] show a MIMO approach for indoor optical wireless communication, [13] studied the capacity of a optical MIMO system and [19] details some work on space-time codes for optical MIMO. Earlier work by Kahn [23] investigates the use of multibeam transmitters and imaging receivers in Infra-Red systems very similar to MIMO in concept. Very recently the PixNet project [20] presents an implementation of an LCD - camera communication system that can deliver high data rates of the order of Mbps over distances of about 16m and wide view angles. PixNet uses OFDM to transmit between the LCD-camera pair similar to the pixelated - MIMO system proposed by Hranilovic and Kschischang [13]. In this paper we will emphasize that regardless of any type of modulation and transmission scheme, visual MIMO can still achieve significantly high data rates by exploiting some of the uniquecharacteristics of the visual channel.III. VISUAL MIMO MODELIn the visual MIMO communications system, the optical transmit element generates a light beam (optical signal) whose output power is proportional to the electrical input power of the modulating signal, limited by the emitter’s peak transmission power [14], [18], [22]. While RF channels are typically characterized by their impulse response that reflects the multipath environment, this aspect differs significantly for optical channels. Since the rate of change of the channel impulse response is very slow compared to the frequency of the optical signal, it is usually sufficient to use a static parameter (channel DC gain) [16] to represent the channel. For the same reason inter-symbol interference and multipath fading can be neglected in optical wireless channels. Similarly Doppler shift is negligible compared to the frequency as well.Consider the visual MIMO communication system model as shown in Fig. 1 where an opticaltransmitter consisting of an array of K transmitting elements communicates to a camera receiver with an array of I J pixels. The channel model for the visual MIMO system is given as,where Y 2 RI J is the image current matrix with eachelement representing the received current y(i; j) in each pixel with image coordinates (i; j), xk 2 R represents the transmitted optical power from kth element of the LEA and Hk 2 RI J is the channel matrix of the kth transmit element of the LEA, with elements hk(i; j) representing the channel between the kth transmit element and pixel (i; j), and N is the noise matrix. Noise in optical wireless is dominated by shot noise from background light sources and typically modeled as AWGN [16], [18]. Each element n(i; j) of the noise matrix N representing the noise current at each pixel is given aswhere q is the electron charge, R is the responsitivity of the receiver characterized as the optical power to current conversion factor, Pn is the background shot noise power per unit area, s is the square pixel side length and W is the sampling rate of the receiver (equates to the frame rate of the camera).The optical signal from the kth transmit element (k =1; 2; 3 : : :K) emitting a light beam of power Pin;k will be transmitted into the channel. At the receiver, depending on the focusing of the camera and the distance between the transmitting element and the camera, the transmitting element’s image may strike a pixel or a group of pixels of the detector array. The signal current in each pixel will depend on the concentration of the received signal component on that pixel which can be quantified as the ratio of the pixel area relative to the area spanned by the transmitting element’s image on the detector. If ck(i; j) represents the concentration ratio of the kth transmit element of an LEA on pixel (i; j), the channel DC gain hk(i; j) from each transmit element k to the pixel(i; j) is given aswhere R is the responsitivity, Ro( ) is the Lambertian radiation pattern of the optical transmitting element [16] with half-power angle , Alens is the area of the camera lens, is the camera field-of-view (fov) and dk;i;j , -k;i;j are the distance & viewing angle between each transmit element kand receiving pixel (i; j) respectively.Typically, since the pixel size is very small (order ofmicrons), the difference in distance dk;i;j and the viewing angle -k;i;j between each element of the transmitter array and every pixel is negligible. Therefore we refer to the distance dk;i;j = d and the viewing angle -k;i;j = - as the perpendicular distance and the angle between the transmitter array and image detector planes respectively. Hence the channel between each transmit element k and each pixel (i; j), characterized by hk(i; j), is primarily dependent on the concentration ratio ck(i; j) which can expressed as,where, s, f, lk are the pixel edge length, camera focal length and diameter of kth transmit element (considering a circular transmitting element) respectively. The amount of concentration of the signal per pixel is also dependent on the amount of blur in the image due to the lens. Typically, lens blur is modeled as a Gaussian function [12] and the amount of blur in the image is quantified by its standard deviation ( blur). The lens essentially acts like a filter with the blur function as its impulse response. Thus the image of the transmit element can be viewed as a result of the projected image convolving with the blur function over the detector area.I(:) is an indicator function indicating whether a pixel (i; j) receives a signal from the transmit element k or not, and is referenced in terms of the distance from pixel at the center of the transmit element’s image (irefk ; jrefk ). Given the spatial coordinates of the transmitting elements of an LEA with respect to the camera reference we can determine the image center coordinates of those transmit element through optical ray-tracing techniques in conjunction with some basic computer vision theory [9].IV. PERSPECTIVE DEPENDENT MIMO GAINSWhile the channel model in (1) resembles that of the familiar RF MIMO channel model, in fact it is significantly different from that. In RF MIMO systems, the channel matrix is typically a rich scattering matrix (usually full rank) whose entries are modeled well as independent and identically distributed random variables [10]. Further, this property allows the RF MIMO system to exploit either diversity and or multiplexing gains in data transmission which primarily depend on the multipath fading in the RF channel. The fact that the communication system here uses light as the communication medium, requires line of sight at the receiver, and the nature of the concentration function of the camera, renders some unique multiplexing and diversity characterizations different from RF MIMO.A. Resolvability of imagesThe notion of ‘parallel’channels to obtain the multiplexing data rate gains can be achieved only if the circumference of two transmit elements as seen on the image plane are separated by atleast a threshold ( ) number of pixels in both dimensions (horizontal and vertical). As we see in Fig. 2 even if the circumference of the two transmit element images are separated by one pixel they may not be resolvable because of the blur in the image. Hence we set a threshold distance of separation between the image circumferences, = 2p 2ln2 blur, equal to the full-width-half maximum (FWHM) of the Gaussian lens-blur function typically used as a parameter for image resolution in analyzing fine detailed astronomical and medical images [4], [5]. The distance of separation between the images of the transmit elements can be determined by perspective projection analysis (as described in [6]) considering circular transmitting elements. Given a fixed-focal length f of the camera, pixel side length s and a spatial distance between the circumference of two adjacent LEDs, the circumference of two transmit element images will be separated by im = fds pixels in each dimension. Therefore the separation between thecircumference of two transmit element images will be equal to the threshold (=s) at a distance d = f between the LEA and camera. This implies that, multiplexing in visual MIMO ispossible only when d d and when d > d each transmit element has to transmit the same information whereby diversity combining at the receiver can ensure an SNR gain and hence an equivalent capacity gain.B. Dependence on viewing angleWe can observe in equation (3) that the channel quality depreciates with the viewing angle - (angle between the camera image plane and LEA surface plane). Two images which are clearly separated in the image plane may look overlapped when viewed from an angle. Such distortions can significantly depreciate the signal quality and the detection capability leading to errors and thus reduction in the data rates. Moreover such an angular view also reduces the achievable multiplexing transmission range. This is because when the camera image detector plane is at an angle - to the transmitter array the effective spatial separation between two neighboringtransmit elements becomes (as shown inFig. 3). From the earlier discussion on the resolvability of images, it implies that the distance upto which multiplexing can be achieved in visual MIMO then reduces toC. Distance dependent MIMO gainsIn the visual MIMO channel, for a static transmitter and receiver, the image of the LEA transmit elements captured by the camera spans one pixel or multiple pixels. Further, the image plane is spanned by images of each transmit element clearly delineated and the size of image span depending on the focus (concentration ratio) of the camera. As illustrated in Fig. 4, at short distances between the transmitter and receiver, each transmitting element of the LEA looks clearly focused on a unique set of pixels and the images of these elements can be detected from the complete image. In contrast, at a large distance between the transmitter and receiver, the image of each transmit element looks clearly unfocused and thus the signal from all the transmitting elements of the LEA is directed to typically one or few pixels. This suggests that at short distances, the system can offer large ”multiplexing” gains by using the transmitting elements to signal independent bitstreams or equivalently realiz ing ”parallel” channels. On the other hand, at large distances, there can only be a ”diversity” gain where by the same bits are signaled on each of the transmit elements. These distance dependent gains in visual MIMO is in contrast to the RF MIMO channel, where the rich scattering channel matrix typically allows a continuous trade-off between diversity and multiplexing gains [24], [27].Fig. 4. Distance dependent Multiplexing and Diversity modesV. VISUAL MIMO CHANNEL CAPACITYTo quantify the perspective dependent multiplexing and diversity gains in visual MIMO we use the channel capacity of the visual MIMO channel as a metric which is given as,where W is the receiver sampling rate (camera frame-rate), d is the threshold multiplexing distance from equation (6). SNRcam;k is the signal-to-noise ratio of the kth LED at the camera receiver [6] which is expressed in terms of the transmit power xk, the channel DC gain hk(i; j) from equation (3) and AWGN noise nk(i; j) from equation (2). I(:) is the indicator function, from equation (5). We plot the channel capacity from equation (7), for an exemplary visual MIMO system, where the transmit elements of the LEA are light emitting diodes (LEDs) and the receiver is a machine vision camera (Basler Pilot piA640), over a range of distances d (Fig. 5) and over different viewing angles -(Fig. 6). The underlying parameters used in our analysis are summarized in Table I. Inferences: From the analytical capacity plots we draw few notable inferences that relate to the multiplexing and diversity characterizations in visual MIMO.The visual MIMO system with no blur can achieve capacities of the order of Mbps even at long distances of about 90m. Blurring certainly reduces multiplexing range but still medium ranges of 30-40m are achievable at high data rates. The data rate gains at these distances are attributed to multiplexing where each LED sends an independent stream of bits over parallel channels. The transitions in the plot (for the multi LED cases) indicate the switch from multiplexing to diversity mode. The capacity gains due to diversity at the long distances, though may not be significant comparable to the multiplexing gains at shorter distances, are still close to an order of magnitude gain compared to the single LED system.Fig. 5. Visual MIMO channel Capacity versus distance (- = 0)Fig. 6. Visual MIMO channel Capacity versus angle (d constant)A visual MIMO system will have to switch between the multiplexing and diversity modes in discrete intervals based on distance and angle unlike RF MIMO where the gains in these modes could be achieved simultaneously but follow a continuous trade-off in performance. Moreover, a visual MIMO system will have to switch autonomously between these modes depending on the orientation of the receiver with respect to the transmitter in order to leverage the gains. This suggests that the throughput of visual MIMO links can be significantly improved through rate adaptation techniques, which adapt the transmission scheme to the receiver perspective. In RF MIMO, in order to select the mode of operation (multiplexing and/or diversity) the channel state information (CSI) has to be known or estimated which either incurs a data overhead and/or complex receiver processing. But in visual MIMO, since the optical channel is deterministic in nature the overhead in selecting either of the modes of operations will be very less because the need to send preamble bits to determine the channel information (distance,angle etc.) may be obviated by the use of efficient computer vision techniques [6]. Since fading is negligible the complexity in estimating the CSI to exploit MIMO techniques is lesser than in RF but still leads to interesting challenges in computer vision and image processing. The visual MIMO channel capacity is consistent over a wide range of viewing angles (small or large depends on distance). We see that the system can achieve large multiplexing gains at short distances and at almost all viewing angles which implies that the system would be robust to any misalignment between the transmitter and receiver. Its cleat that at large distances (of the order of 75m), due to the effect of lens blur, the LEDs may not be resolved easily even at - = 0 and hence at such distances where multiplexing will fail but using diversity over all angles can still offer an order of gain in data rates. Such consistency in data rates over angular misalignment is important especially in mobile settings as the choice of multiplexing and/or diversity depends largely on the orientation of the优于光电二极管接收器的信道容量在中长期范围。
短距离无线数据传输系统的设计实现
短距离无线数据传输系统的设计实现
王延华;岳林
【期刊名称】《机械工程与自动化》
【年(卷),期】2009(000)005
【摘要】介绍了一个基于nRF2401A射频芯片的短距离无线数据传输系统,通过AT89C52单片机控制射频芯片nRF2401A,实现2个射频芯片之间在ShockBurstTM模式下进行数据的发射与接收,同时接收方通过AT89C52单片机的串口将接收到的数据经RS232接口电平转换后传给主机.通过实验分析了无线数据传输系统的性能、主要影响因素以及系统的稳定性.
【总页数】4页(P33-35,38)
【作者】王延华;岳林
【作者单位】南京航空航天大学,机电学院,江苏,南京,210016;南京航空航天大学,机电学院,江苏,南京,210016
【正文语种】中文
【中图分类】TN919.6
【相关文献】
1.解读ZigBee技术的短距离无线数据传输系统 [J], 阮家健
2.短距离无线数据传输系统研究 [J], 周黎明
3.短距离无线数据传输系统的设计 [J], 朱宏伟;马悦;;
4.短距离无线数据传输系统的设计 [J], 朱宏伟;马悦
5.短距离无线数据传输系统研究 [J], 张浩锐
因版权原因，仅展示原文概要，查看原文内容请购买。
毕业设计之基于NRF24L01的IMU数据无线传输系统设计样本
接收端单片机C8051F020能够经过输入Ｃ语言程序对无线射频芯片NRF24L01参数就行设置，设为接收模式以接收检验信号。接收到检验信号后，NRF24L01自动应答功效会发送应答信号给发送端已确定收到信号，接着NRF24L0其传送给上位机。
2.2方案介绍
2.2.1方案整体设计思绪
经过单片机(C8051F020)将IMU单元输出六路模拟数据采集，再利用单片机内部AD转换部分将模拟信号转换成数字信号，然后经过SPI总线将数据传输给无线发送芯片(NRF24L01),无线发送芯片将数据发送出去。一样，接收端单片机(C8051F020)经过SPI总线控制接收端芯片，将无线传输过来数据接收，并将数据传送给上位机，从而实现了对IMU数据采集、转换、无线传输、和存放。
无线数据传输就是指利用无线电波作为数据传输媒介，将当地计算机或其它设备数据信息调制到载波频率上发射，从而和远程终端之间实现通讯技术[6]。它包含到计算机技术、信息技术、和网络技术等多个学科领域。经过无线传输系统，大家能够获取远端设备运行情况和多种参数指标，经过对采集到数据分析从而实现远程管理、远程控制等功效。
设 计 题 目：
基于NRF24L01IMU数据无线传输系统设计
1月18日
毕业设计开题报告
1．结合毕业设计情况，依据所查阅文件资料，撰写字左右文件综述：
文献综述
1.1数据无线传输系统设计研究背景
数据是指用来描述客观事物数字、字母、符号等等[1]，伴随科技进步，人类社会已经进入了数字化信息化时代，所以数据传输质量和速度全部提出了更高要求。针对现在信息化情况，原有有线传输系统虽完成了数字化和网络化，但复杂布线、高昂维护成本使网络节点分布范围受到了很大限制，这在很大程度上阻碍了数据传输信息化深入和普及。所以，对于无线数据传输需求日益迫切。
基于nRF24L01的无线短距离图像传输系统
中国科技期刊数据库 工业A2015年18期 299基于nRF24L01的无线短距离图像传输系统宋则宇武汉理工大学，湖北 武汉 430070摘要：随着时代的发展，图像数据的采集和传输在科学研究、工农业生产、医疗卫生和公共安全等领域得到了越来越广泛的应用，而这些工作都需要一套高速的数字图像采集系统来完成。
同时图像的采集和传输也是进行图像处理、图像压缩、图像识别的基础，所以对无线图像传输系统的研制有着重要的现实意义和价值。
目前的图像采集设备大都要通过计算机接口将图像数据传输到计算机中，借助计算机的高运算速度和大存储容量完成图像采集工作。
传统的计算机接口在处理图像数据传输时存在成本高、使用不便等问题。
本文设计了一套基于nRF24L01的无线短距离图像传输系统，利用ATmega128控制FIFO 缓冲器AL422B 时序采集数字摄像头OV6620的图像采集，并通过nRF2401进行无线数据发送，并在计算机上进行图像显示。
本文研究了OV6620的图像数据存储的方法和原理，以及无线收发数据的实现。
经评估，本系统成本低廉、系统稳定、安全性好，具有广泛的应用价值。
关键词：图像采集；OV6620；AL422B ；nRF24L01；无线图像传输 中图分类号：TP273 文献标识码：A 文章编号：1671-5799(2015)18-0299-021 绪论图像信号是人们进行交流的基础，视觉信息是人们活动的基本内容。
从古以来人们就希望“亲眼所见”，随着模拟电子技术的出现和发展，人们开始研发模拟电子产品来实现模拟视频信号存储和传输。
这样使“亲眼所见”在空间上和时间上得到了极大的改善，人们可以不在现场或不见面就亲眼见到现场的视觉信息。
随着各种电子技术的发展，特别是数字电子技术的发展以及全球数字化进程的推进，视频的采集设备和方式都有了很大的发展，直接采集视频的设备也得到了广泛的开发和应用。
现在已经有不少的国内外企业或公司开发了一些用于某种专门用途的数字化视频设备，随着高性能专用无线射频芯片的研发问世，以及相关短距离无线通信技术的发展，短距离无线通讯已经成为了当前人们讨论的一个热门话题。
开题报告-吕彦飞-06221098_1_
学院：机械与电子控制工程学院专业：测控技术与仪器
学生姓名：吕彦飞学号：06221098
1.1课题的研究背景
随着社会经济的飞速发展和人民物质生活水平的不断提高，人们对其住宅的要求也越来越高，表现在不仅希望拥有舒适、温馨的住所，而且对其安全性、智能性等方面也提出了更高的要求。然而经济的快速增长也带来了相当大的负面社会效应，城乡、区域收入差距进一步拉大，社会结构、社会治安日趋复杂，社会矛盾开始凸显[1]。随着流动人口迅速增加，盗窃、入室抢劫等刑事案件也呈现出了增长趋势，并且危害越来越严重，人们越来越渴望有一个安全生活的空间，但是犯罪分子的作案手段越来越高明，他们甚至采用一些高科技的作案手段，使得以往那种依靠安装防盗门窗、或靠人防的防范方式越来越不能满足人们日常防范的要求；这时，传统的家庭住宅显然己经远远不能满足人们的需求[2]。人们迫切需要一种智能型的家庭安全防范报警系统，能可靠的进行日常安全防范工作，及时发现各种险情并通知户主，以便将险情消灭在萌芽状态，这样人们便可安心工作，同时也保证了居民的生命财产不受损失。于是有关家庭、办公室和仓库等处的安全防范和自动报警系统的开发研制日益被科研单位和生产厂家所重视，现在市场上也出现了各种名目繁多的报警装置，但多由于可靠性较差、造价高或使用复杂而难于普及[3]。而随着电子通讯技术的飞速发展，单片微机以其具有体积小、价格低、集成度高、性价比高等突出优点已在工业控制、智能仪表、数控机床、数据采集以及各种家用电器等方面得到了广泛应用。因此利用单片机和一些简单的外围器件来开发一种适合于家庭、仓库、银行等重要场所的低价位、运行可靠的多功能智能型安全防范报警系统，对室内出现的入室盗窃事件自动发出报警信息并通知户主进行及时处理已经势在必行[4]。
1.2防盗报警系统的国内外研究现状
2018-开题报告201X4429 (1000字)-范文模板 (2页)
2018-开题报告201X4429 (1000字)-范文模板
本文部分内容来自网络整理，本司不为其真实性负责，如有异议或侵权请及时联系，本司将立即删除！
== 本文为word格式，下载后可方便编辑和修改！ ==
开题报告201X4429 (1000字)
毕业设计(论文) 开题报告
学生姓名：苏元龙学号： 201X4429 学院：理学院
专业：地理信息系统设计(论文)题目：基于对象的遥感图像地物分割研究指导教师：刘峰
201X年 4月 12日
开题报告填写要求
1．开题报告（含“文献综述”）作为毕业设计（论文）答辩委
员会对学生答辩资格审查的依据材料之一。
此报告应在指导教师指导下，由学生在毕业设计（论文）工作前期内完成，经指导教师签署意见及所在专业审查后生效；
2．开题报告内容必须用黑墨水笔工整书写或按教务处统一设
计的电子文档标准格式（可从教务处网页上下载）打印，禁止打印在其它纸上后剪贴，完成后应及时交给指导教师签署意见；
3．“文献综述”应按论文的格式成文，并直接书写（或打印）
在本开题报告第一栏目内，学生写文献综述的参考文献应不少于15篇；
4．有关年月日等日期，按照如“201X年4月26日”方式填
写。
∙荐全国教育科学规划课题开题报告
∙荐县城区“村改居”工作实施方案
∙荐技术创新预测与评估模型及其应用研究开题报告
∙荐植物营养学专业硕士研究生培养方案
∙荐《在网络环境下基本教育模式的研究》课题开题报告。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
福建农林大学
毕业设计开题报告
设计题目：简易短距离无线图传系统
的设计
姓名：吕东旭
专业年级：12级电子科学与技术
学号：3126110023
指导教师：梁真
时间： 2016年 3 月14 日
一、本设计课题的目的意义
本次设计利用新型视频字符叠加芯片MAX7456和超声波测距传感器构成一款可图文并茂的图像传输系统，不仅可以获取摄像头传输的图像内容，而且能够显示超声波传感器所采集到的距离信息，直观观察目标的实时情况。
并且利用无线传输技术，使安装更加便捷，出现故障时也比较容易排除。
本设计可应用于倒车雷达，航空拍摄等方面，相较于传统的有线倒车雷达，本设计使用起来将更加方便。
若用于航空拍摄时，则可以将现场的实时图像传输回指挥中心，使指挥中心的人员如身临其境，提高决策的准确性和及时性，提高工作效率。
二、本设计课题的主要设计内容、预期设计结果和拟解决的关键问题
本课题设计主要实现图像的短距离无线电传输显示功能，将摄像头采集到的视频图像新号和超声波测距传感器的数据信息，通过无线传输模块传送到终端进行显示，其中测距得到数据等文字信息能同图像一起叠加显示。
需要解决的关键问题为：
1.文字信息和图像的叠加显示；
2.短距离无线传输模块的设计；
3.超声波测距功能的实现；
4.距离数据的实时显示。
三、设计方法和步骤
设计方法：采用软硬件结合的方法，将整个设计分为三个模块：测距模块、叠加模块和传输模块。
用单片机来实现测距模块的控制，叠加芯片MAX7456控制叠加模块，最后通过无线传输来实现显示。
设计步骤：
1.收集MAX7456芯片和超声波测距传感器的资料；
2.设计传感器测距电路，实现距离的探测；
3.设计单片机模块，控制所要叠加的数据，传输至MAX7456中；
4.设计叠加模块，实现图像信息和数据信息的叠加；
5.编写相应的程序；
6.模拟仿真；
7.做出实物并调试；
8.完成论文。
四、设计工作的总体安排及进度
2016.03.01～2016.03.15 搜集和阅读相关的文献资料，初步了解系统设计的基本思想，完成论文的开题报告；
2016.03.16～2016.03.31认真阅读搜集到的资料，初步完成系统的硬件设计与软件设计，并完成论文的大纲；
2016.04.01～2016.04.20 完成系统整体设计，并形成论文初稿；
2016.04.21～2016.04.30 对系统的软、硬件部分进行调试；
2016.05.01～2016.05.10 总体设计结束，并形成最终论文。
指导教师审查意见：
签字：
年月日系(教研室)审查意见：
签字：
年月日学院审查意见：
分管院长签章：
年月日。