【摘要】：伴隨微電子技術(shù)迅猛發(fā)展,導(dǎo)航技術(shù)的應(yīng)用領(lǐng)域已漸漸從軍事化轉(zhuǎn)向了商用化。近幾年,室內(nèi)導(dǎo)航技術(shù)得到了大力發(fā)展,受到了越來越多企業(yè)和民眾的重視。但現(xiàn)有的室內(nèi)定位系統(tǒng)多是基于基礎(chǔ)設(shè)施實(shí)現(xiàn),其缺點(diǎn)非常明顯：需要提前在需要導(dǎo)航定位的環(huán)境中安裝大量外部設(shè)備,投入成本不菲,且精度仍有待提高。本文擬設(shè)計(jì)一種基于自身傳感器的行人導(dǎo)航系統(tǒng)來解決上述缺陷。 捷聯(lián)式慣性導(dǎo)航技術(shù)不僅可以避免需要外設(shè)、投入高等缺陷,并且在短時(shí)間定位精度相當(dāng)高,但隨著時(shí)間的推移,其存在累積的漂移誤差。針對(duì)這一點(diǎn),本文基于卡爾曼濾波設(shè)計(jì)出一種有效補(bǔ)償累積誤差的算法。首先,通過捷聯(lián)式慣性計(jì)算模塊對(duì)慣性測(cè)量信息進(jìn)行積分解算,由角速度積分求解出姿態(tài)信息,通過四元數(shù)法對(duì)加速度進(jìn)行坐標(biāo)轉(zhuǎn)換,而后積分求解出速度信息,再二次積分求解出位置信息；然后,由零速檢測(cè)模塊通過三條件判斷法對(duì)行人步行時(shí)的“零速度”階段進(jìn)行檢測(cè),當(dāng)檢測(cè)到“零速度”時(shí)觸發(fā)卡爾曼濾波模塊；最后,將捷聯(lián)式慣性計(jì)算后的速度向量作為量測(cè)值,使用卡爾曼濾波來估計(jì)系統(tǒng)狀態(tài)誤差,通過求解出的速度估計(jì)協(xié)方差,對(duì)狀態(tài)誤差估計(jì)進(jìn)行分段,融入后向固定區(qū)間平滑技術(shù),進(jìn)一步調(diào)整狀態(tài)誤差估計(jì)及其協(xié)方差矩陣,前向反饋校正行人位置、速度和姿態(tài)信息；同時(shí),擴(kuò)充了卡爾曼濾波狀態(tài)模型,加入加速度計(jì)和陀螺儀的零偏誤差信息,通過反饋校正慣性測(cè)量信息,進(jìn)一步消除系統(tǒng)漂移誤差,最終實(shí)現(xiàn)了室內(nèi)環(huán)境的行人定位導(dǎo)航。 在上述誤差補(bǔ)償算法的基礎(chǔ)上,本文設(shè)計(jì)了一種行人導(dǎo)航系統(tǒng),通過多組實(shí)驗(yàn)仿真驗(yàn)證,在500m路程內(nèi),該行人導(dǎo)航系統(tǒng)收斂在穩(wěn)定狀態(tài),定位精度保持在1m之內(nèi),實(shí)現(xiàn)了高精度的定位目標(biāo)。 本文設(shè)計(jì)的行人導(dǎo)航系統(tǒng),為基于自身傳感器的室內(nèi)定位提供了一種簡單而有效的方法,可以進(jìn)一步融合完善,并推廣應(yīng)用到智能家居、火場(chǎng)救援、超市購物、車庫停車等諸多場(chǎng)景之中。
[Abstract]:With the rapid development of microelectronics technology, the application field of navigation technology has gradually changed from militarization to commercialization. In recent years, indoor navigation technology has been greatly developed by more and more enterprises and people. However, most of the existing indoor positioning systems are based on infrastructure, and their shortcomings are very obvious: a large number of external devices need to be installed in advance in the environment where navigation and positioning is needed, the cost of investment is very high, and the precision still needs to be improved. This paper proposes to design a pedestrian navigation system based on its own sensor to solve the above shortcomings. Strapdown inertial navigation technology can not only avoid the need for peripherals, put in high defects, and in a short time positioning accuracy is quite high, but with the passage of time, it has accumulated drift error. In view of this, this paper designs an effective algorithm to compensate cumulative error based on Kalman filter. Firstly, the inertial measurement information is solved by the strapdown inertial calculation module, the attitude information is obtained by the angular velocity integral, the acceleration is transformed by the quaternion method, and the velocity information is obtained by the integration. Secondly, the position information can be solved by quadratic integration. Then, the zero-speed detection module is used to detect the "zero-speed" phase of pedestrian walking through three-condition judgment method, and the Kalman filter module is triggered when the "zero-speed" is detected. Finally, the velocity vector calculated by strapdown inertia is used as the measurement value, and Kalman filter is used to estimate the state error of the system. By solving the covariance of velocity estimation, the state error estimation is segmented. Further adjust the state error estimation and its covariance matrix with backward fixed interval smoothing technology, and forward feedback corrects pedestrian position, velocity and attitude information. At the same time, the Kalman filter state model is extended, the zero bias error information of accelerometer and gyroscope is added, and the inertial measurement information is corrected by feedback to further eliminate the drift error of the system. Finally, the pedestrian positioning and navigation in indoor environment is realized. Based on the error compensation algorithm mentioned above, a pedestrian navigation system is designed in this paper. It is verified by many experiments that the pedestrian navigation system converges to a stable state and the positioning precision is kept within 1m within 500m distance. The high precision positioning target is achieved. The pedestrian navigation system designed in this paper provides a simple and effective method for indoor positioning based on its own sensor, which can be further integrated and applied to smart home, fire rescue, supermarket shopping, Garage parking and many other scenes.
【學(xué)位授予單位】：廈門大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN966

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