本文關(guān)鍵詞： 隔墻 人體運(yùn)動(dòng)檢測 信號(hào)處理 軟件無線電　出處：《浙江大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近十年來的隔墻人體運(yùn)動(dòng)檢測技術(shù)主要使用超寬帶信號(hào),但往往需要用GHz的帶寬、較高的功率才能分辨出墻后的物體,且一般雷達(dá)系統(tǒng)體積較大。如果能夠不使用超寬帶信號(hào),而采用基于工業(yè)、科學(xué)和醫(yī)藥(Industrial Scientific Medical,ISM)頻段信號(hào)來實(shí)現(xiàn)一種小帶寬、小功率、小體積、低成本的隔墻人體運(yùn)動(dòng)檢測系統(tǒng),將對(duì)社會(huì)公共安全以及人民生活的方方面面產(chǎn)生極大的影響。本文對(duì)隔墻人體運(yùn)動(dòng)檢測技術(shù)進(jìn)行了深入探究,設(shè)計(jì)實(shí)現(xiàn)了基于ISM頻段信號(hào)的隔墻人體運(yùn)動(dòng)檢測系統(tǒng)。本文主要工作包括:1.設(shè)計(jì)了隔墻人體運(yùn)動(dòng)檢測系統(tǒng)。首先研究墻體等強(qiáng)背景噪聲干擾下的隔墻人體運(yùn)動(dòng)檢測機(jī)理;然后采用IEEE 802.11n信號(hào)進(jìn)行通信,并利用預(yù)編碼來消除墻體等靜態(tài)物體反射回來的強(qiáng)干擾信號(hào),從而能夠提取出墻后微弱的人體運(yùn)動(dòng)回波信號(hào);最后使用軟件無線電設(shè)備及平臺(tái)實(shí)現(xiàn)了信號(hào)收發(fā)以及背景噪聲干擾抑制,并對(duì)干擾抑制效果進(jìn)行分析,得出其抑制效果有一個(gè)上限。2.研究隔墻人體運(yùn)動(dòng)檢測的離線信號(hào)處理方法。通過對(duì)接收信號(hào)進(jìn)行時(shí)域、頻域和聯(lián)合時(shí)頻域信號(hào)處理與分析比較,可以提取出用于隔墻檢測使用的特征屬性,進(jìn)而提出了基于閾值的隔墻人體運(yùn)動(dòng)檢測方法。為了適用于不同的檢測環(huán)境,引入機(jī)器學(xué)習(xí)的思想,提出了基于聚類和分類的隔墻人體運(yùn)動(dòng)自適應(yīng)檢測方法。3.研究隔墻人體運(yùn)動(dòng)朝向檢測的離線信號(hào)處理方法。從接收信號(hào)中提取出信道狀態(tài)信息,進(jìn)而獲取多普勒頻移以判斷運(yùn)動(dòng)人體相對(duì)接收機(jī)的運(yùn)動(dòng)方向;且通過頻偏可以大致估算出人體的運(yùn)動(dòng)速度。另外,通過使用動(dòng)態(tài)時(shí)間規(guī)整算法能夠檢測區(qū)分出沿墻水平和垂直運(yùn)動(dòng)兩種運(yùn)動(dòng)朝向。4.研究隔墻人體實(shí)時(shí)檢測的信號(hào)處理方法,并設(shè)計(jì)結(jié)果展示界面。首先通過對(duì)離線方法進(jìn)行修改,并輔助輕量級(jí)檢測方法,能夠給出更短時(shí)間內(nèi)的運(yùn)動(dòng)模式信息;然后設(shè)計(jì)了結(jié)果展示界面及離線分析工具;最后對(duì)檢測準(zhǔn)確性進(jìn)行了分析討論。
[Abstract]:In recent ten years, the human motion detection technology of partition wall mainly uses UWB signal, but it often needs the bandwidth of GHz and the higher power to distinguish the object behind the wall, and the general radar system is larger. If UWB signal can not be used, A small bandwidth, small power, small volume and low cost partition wall human motion detection system is realized by using industrial, scientific and pharmaceutical industrial Scientific frequency band signals. Will have a great impact on social public safety and all aspects of people's life. A human motion detection system based on ISM frequency band signal is designed and implemented. The main work of this paper includes: 1. A human motion detection system is designed. Firstly, the mechanism of human motion detection under strong background noise is studied. Then the IEEE 802.11n signal is used to communicate, and the strong interference signal reflected from the static object such as the wall is eliminated by precoding, which can extract the weak echo signal of human body behind the wall. Finally, the software radio equipment and platform are used to realize the interference suppression of signal transceiver and background noise, and the effect of interference suppression is analyzed. It is concluded that there is an upper limit. 2. The off-line signal processing method for human motion detection of partition wall is studied. The signal processing in time domain, frequency domain and joint time and frequency domain is compared with the received signal, and compared with the received signal in time domain, frequency domain and joint time and frequency domain. The feature attributes used in partition wall detection can be extracted, and then a threshold based human motion detection method is proposed. In order to be suitable for different detection environments, the idea of machine learning is introduced. In this paper, an adaptive detection method of human motion based on clustering and classification is proposed. 3. The off-line signal processing method for detecting human motion orientation of partition wall is studied. The channel state information is extracted from the received signal. Then the Doppler frequency shift is obtained to judge the moving direction of the moving human body relative to the receiver, and the motion velocity of the human body can be roughly estimated by the frequency offset. By using dynamic time warping algorithm, we can detect and distinguish two kinds of moving directions. 4. The signal processing method of real time detection of human body with partition wall is studied, and the result display interface is designed. Firstly, the off-line method is modified. With the help of lightweight detection method, the motion mode information can be given in a shorter time. Then the result display interface and off-line analysis tool are designed. Finally, the accuracy of the detection is analyzed and discussed.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN911.7

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本文編號(hào)：1514679