本文選題：指紋識別 + 反饋電容式　； 參考：《電子科技大學(xué)》2016年碩士論文

【摘要】：隨著集成電路的發(fā)展和物聯(lián)網(wǎng)的興起,生物識別技術(shù)在個人認(rèn)證中的應(yīng)用變得越來越重要、越來越廣泛了。其中指紋識別是眾多生物識別技術(shù)中發(fā)展最為成熟的技術(shù),應(yīng)用也是最廣泛的現(xiàn)在。超聲波式指紋識別還處在研發(fā)階段,而射頻式只有少數(shù)廠家掌握,所以市場上的半導(dǎo)體指紋傳感器主要還是電容式的。電容式指紋傳感器兼具體積小、靈敏度高、仿假手指等優(yōu)點。反饋電容式指紋識別相對于普通的電容式具有更高的靈敏度的優(yōu)點。本文主要是對反饋電容式指紋識別的模擬電路部分進行了設(shè)計。該傳感器的數(shù)字輸出為8位,將手指與芯片的距離量化為256個灰度值。文章首先對指紋識別的種類和發(fā)展歷史作了簡要的介紹。緊接著,詳細(xì)地介紹了反饋電容式指紋識別的工作原理。在對電路模塊進行設(shè)計前,我們必須有一個問題需要解決。由于在電路模型中,手指和芯片形成的電容中存在邊緣電場電容,而該電容很難通過手工計算獲得。所以文章先利用ANSYS Maxwell軟件對手指芯片距離和電容的關(guān)系進行了模擬。傳感器模擬部分主要分為采集單元、可變增益放大器、8位Pipeline ADC、環(huán)形振蕩器和其他一些輔助電路�？紤]到面積原因,采集單元沒有采用運算放大器,而是運用共源共柵放大器結(jié)構(gòu),增益在70dB以上�？勺冊鲆娣糯笃鞑捎梅答侂娮枋�,通過改變接入電路的電阻大小,從而改變電路增益,可變增益的范圍為1到2.4,步長為0.2。8位ADC采用Pipeline結(jié)構(gòu),一共分為兩級,第一級4位,第二級5位,多的一位做數(shù)字校正用,采樣頻率為1MHz。環(huán)形振蕩器主要為系統(tǒng)提供時鐘,有三種頻率提供選擇,分別為12MHz、16MHz、22MHz。其他的一些輔助電路包括跟隨器、寄存器和選擇電路等等。本文采用0.5?m工藝,利用Spectre對電路進行了仿真。通過整體仿真獲得手指與芯片距離的關(guān)系和灰度值的關(guān)系圖。最后經(jīng)過流片測試驗證,各個電路模塊能正常工作,指紋圖像清晰。
[Abstract]:With the development of integrated circuits and the rise of Internet of things, the application of biometrics in personal authentication has become more and more important and extensive. Fingerprint identification is the most mature technology in many biometric technologies, and its application is the most extensive now. Ultrasonic fingerprint identification is still in the research and development stage, but only a few manufacturers control the RF type, so the semiconductor fingerprint sensor in the market is mainly capacitive. Capacitive fingerprint sensor has the advantages of small size, high sensitivity and fake finger. Feedback capacitive fingerprint recognition has higher sensitivity than conventional capacitance. In this paper, the analog circuit of feedback capacitive fingerprint identification is designed. The digital output of the sensor is 8 bits and the distance between finger and chip is quantified to 256 gray values. First of all, this paper briefly introduces the types and development history of fingerprint recognition. Then, the working principle of feedback capacitive fingerprint identification is introduced in detail. Before we design the circuit module, we must have a problem to solve. In the circuit model, there is an edge electric field capacitance in the capacitance formed by finger and chip, which is difficult to be obtained by manual calculation. So the relationship between distance and capacitance of finger chip is simulated by ANSYS Maxwell software. The sensor simulation is mainly divided into acquisition unit, variable gain amplifier (VGA) and 8-bit pipeline ADCC, ring oscillator and some other auxiliary circuits. Considering the area reason, the acquisition unit does not use an operational amplifier, but uses a common-gate amplifier structure with a gain of more than 70dB. The variable gain amplifier adopts feedback resistor type, and changes the circuit gain by changing the resistance of the access circuit. The variable gain range is 1 to 2.4, the step size is 0.2.8 bits ADC adopts pipeline structure, which is divided into two levels, the first stage is 4 bits. The second level 5 bit, more than one digit for digital correction, sampling frequency of 1 MHz. The ring oscillator mainly provides the clock for the system, and there are three frequencies to choose from, which are 12MHz / 16MHz / 22MHz. Other auxiliary circuits include followers, registers, and selection circuits. In this paper, the circuit is simulated by Spectre using 0.5m process. The relationship between finger and chip distance and the relationship between gray value and finger are obtained by whole simulation. Finally, the circuit module works well and the fingerprint image is clear.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP212;TN402

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