本文關(guān)鍵詞： 多源傳感器 數(shù)據(jù)融合 自主穩(wěn)定跟蹤 抗干擾　出處：《中國科學(xué)院長春光學(xué)精密機(jī)械與物理研究所》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：光學(xué)測量系統(tǒng)是靶場試驗中用于目標(biāo)捕獲、跟蹤和測量的常用設(shè)備。主要通過光學(xué)成像技術(shù)對空間飛行目標(biāo)進(jìn)行跟蹤測量,獲得靶場目標(biāo)的高精度彈道數(shù)據(jù)和飛行實況影像,為武器鑒定和故障分析提供重要的數(shù)據(jù)。集多種工作波段光學(xué)傳感器為一體的光電經(jīng)緯儀跟蹤系統(tǒng),充分利用多傳感器信息進(jìn)行目標(biāo)跟蹤,可以達(dá)到單一傳感器跟蹤方式無法企及的效果。目前,多傳感器數(shù)據(jù)融合技術(shù)大多用于提高目標(biāo)定位精度,研究該技術(shù)在提高跟蹤穩(wěn)定性和抗干擾能力方向上應(yīng)用的文獻(xiàn)較少。本文以靶場光電跟蹤系統(tǒng)為研究平臺,致力于通過多源傳感器的數(shù)據(jù)融合技術(shù)提高跟蹤系統(tǒng)的抗干擾能力和跟蹤穩(wěn)定性。本文主要研究內(nèi)容和成果如下。1.對多傳感器數(shù)據(jù)融合自主穩(wěn)定跟蹤的相關(guān)理論進(jìn)行了闡述,包括多波段和多參數(shù)光學(xué)傳感器數(shù)據(jù)的融合原理、常用的多傳感器數(shù)據(jù)融合目標(biāo)跟蹤算法以及光電自主穩(wěn)定跟蹤的意義和目的等。根據(jù)實際跟蹤場景中各光學(xué)傳感器的圖像特征和跟蹤數(shù)據(jù)特點,總結(jié)出了光電經(jīng)緯儀自主穩(wěn)定跟蹤的常見影響因素和對應(yīng)的數(shù)據(jù)變化特點。2.研究并改進(jìn)了具有容錯性的多源傳感器數(shù)據(jù)融合算法。介紹了光學(xué)傳感器脫靶量預(yù)處理和經(jīng)緯儀過零點處理的解決方案。改進(jìn)了原基于估計誤差協(xié)方差的數(shù)據(jù)融算法,提出最小二乘曲線擬合與記憶衰減因子相結(jié)合的誤差估計方法,提高了誤差估計的準(zhǔn)確性和實時性。并在融合算法基礎(chǔ)上加入了去野值和防發(fā)散的處理過程。3.研究并提出了基于數(shù)據(jù)融合的多傳感器自主穩(wěn)定跟蹤算法。根據(jù)跟蹤系統(tǒng)的主要目的,將自主跟蹤策略分為目標(biāo)優(yōu)先多傳感器自主選擇跟蹤算法和精度優(yōu)先多傳感器自主協(xié)同跟蹤算法。4.對數(shù)據(jù)融合算法和目標(biāo)優(yōu)先自主選擇跟蹤算法的實驗結(jié)果進(jìn)行了仿真分析和對比。仿真結(jié)果表明,改進(jìn)后的數(shù)據(jù)融合算法在容錯性能和跟蹤精度上均有一定提高,自主選擇跟蹤算法可達(dá)到滿意的數(shù)據(jù)選擇效果。結(jié)合實際跟蹤數(shù)據(jù),分析了數(shù)據(jù)融合算法和兩種自主穩(wěn)定跟蹤算法的實驗結(jié)果。本文全面完整地論述了多傳感器數(shù)據(jù)融合自主穩(wěn)定跟蹤算法的目的、原理和實現(xiàn)方法,最后將本文的數(shù)據(jù)融合及自主跟蹤算法應(yīng)用在某靶場大型光學(xué)測量設(shè)備中,證明了上述算法的有效性和實用性。
[Abstract]:Optical measurement system is commonly used in target acquisition, tracking and measurement in range test. To provide important data for weapon identification and fault analysis. The photoelectric theodolite tracking system, which integrates optical sensors in various working bands, makes full use of multi-sensor information for target tracking. At present, the multi-sensor data fusion technology is mostly used to improve the accuracy of target location. The application of this technique in improving tracking stability and anti-jamming ability is less. In this paper, the photoelectric tracking system of shooting range is used as the research platform. The main contents and achievements of this paper are as follows: 1. The related theory of autonomous stable tracking of multi-sensor data fusion is described. Including multi-band and multi-parameter optical sensor data fusion principle, The commonly used multi-sensor data fusion target tracking algorithm and the significance and purpose of optoelectronic autonomous and stable tracking. According to the image features and tracking data characteristics of each optical sensor in the actual tracking scene, This paper summarizes the common influencing factors and the corresponding data change characteristics of the photoelectric theodolite autonomous stable tracking. 2. The data fusion algorithm of multi-source sensor with fault tolerance is studied and improved. The optical sensor miss distance preposition is introduced. An improved data fusion algorithm based on estimation error covariance. An error estimation method combining least square curve fitting with memory attenuation factor is proposed. The accuracy and real-time performance of error estimation are improved, and the processing process of outliers and anti-divergence is added to the fusion algorithm. 3. A multi-sensor autonomous stable tracking algorithm based on data fusion is studied and proposed. The main purpose of the tracer system, The autonomous tracking strategy is divided into target first multi-sensor autonomous selection tracking algorithm and precision priority multi-sensor autonomous cooperative tracking algorithm .4.The experimental results of data fusion algorithm and target first autonomous selection tracking algorithm are carried out. The simulation results show that, The improved data fusion algorithm has improved both fault-tolerant performance and tracking accuracy, and the self-selection tracking algorithm can achieve satisfactory data selection effect. The experimental results of the data fusion algorithm and two autonomous stable tracking algorithms are analyzed. The purpose, principle and implementation of the multi-sensor data fusion autonomous stability tracking algorithm are discussed in this paper. Finally, the data fusion and autonomous tracking algorithms are applied to a large optical measuring equipment in a range, which proves the validity and practicability of the above algorithms.
【學(xué)位授予單位】：中國科學(xué)院長春光學(xué)精密機(jī)械與物理研究所
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TP212.9

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