侯軼群,鄒 璇,姜 偉,陳 亮,朱佳志
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自然水體中超聲波標(biāo)記魚游動(dòng)軌跡精密確定算法
侯軼群1,2,鄒 璇1,3,姜 偉1※,陳 亮4,朱佳志1
(1. 三峽工程魚類資源保護(hù)湖北省重點(diǎn)實(shí)驗(yàn)室,中國三峽集團(tuán)中華鱘研究所,宜昌 443100; 2. 水利部中國科學(xué)院水工程生態(tài)研究所,武漢 430079; 3. 武漢大學(xué)衛(wèi)星導(dǎo)航定位技術(shù)研究中心,武漢 430079;4. 千尋位置網(wǎng)絡(luò)有限公司,上海 200438)
針對(duì)魚類關(guān)鍵生境位置確定的應(yīng)用需求,該文提出了一套適用于自然水體的超聲波標(biāo)記魚定位算法,解決了標(biāo)記魚定位以及存在粗差觀測值,即水聽器記錄的超聲波信號(hào)接收時(shí)間存在錯(cuò)誤情況下算法的抗干擾性。宜昌黃柏河的實(shí)測結(jié)果表明,基于現(xiàn)有1 ms級(jí)精度的水聽器,可在自然水體中獲得2.15 m精度的信號(hào)標(biāo)記魚三維游動(dòng)軌跡。如因氣泡、遮擋等因素對(duì)水聽器觀測數(shù)據(jù)引入粗差,當(dāng)粗差量級(jí)在10 m以上,該方法可接近100%探測出是否存在粗差。當(dāng)粗差觀測值在3個(gè)以內(nèi)時(shí),該方法的探測成功率可達(dá)84.3%以上,3個(gè)以上時(shí)粗差探測成功率明顯下降,5個(gè)及以上,即粗差觀測值個(gè)數(shù)占觀測值總數(shù)的比例大于31.25%時(shí),基本只能探測出觀測數(shù)據(jù)中存在粗差而無法有效確定粗差。該研究可為漁業(yè)增殖、魚類棲息地保護(hù)、魚類洄游通道等研究提供參考。
位置確定;超聲波;算法;魚;自然水體;距離交匯;游動(dòng)軌跡;粗差探測
在漁業(yè)增殖及魚類保護(hù)領(lǐng)域,行為分析是各項(xiàng)研究的基礎(chǔ)[1-2],魚類位置確定是行為分析的必備手段[3]。隨著科技發(fā)展,魚類定位精度不斷提升。如用機(jī)器視覺和圖像處理技術(shù)可在實(shí)驗(yàn)室條件下有效獲取魚游位置[4],但在自然水體中的魚類定位仍較為困難。一方面自然水體渾濁、光波衰減嚴(yán)重[5],光學(xué)攝像在水下可視范圍小、視覺影像模糊[6];另一方面自然水體流速快、氣泡多、雜質(zhì)多,魚體形態(tài)和游動(dòng)方向隨時(shí)發(fā)生變化,魚探儀等聲學(xué)探測儀器也難以有效跟蹤到魚體的游動(dòng)軌跡[7]。因此,肉眼、視頻拍攝及聲學(xué)探測等方法均難以在自然水體中定量魚體的實(shí)時(shí)動(dòng)態(tài)位置,制約了魚類生態(tài)行為學(xué)的發(fā)展。如:產(chǎn)卵場主要通過對(duì)早期發(fā)育魚卵進(jìn)行捕撈的方式推求。對(duì)于卵苗可在江底直接撈取的中華鱘,據(jù)報(bào)道產(chǎn)卵范圍在葛洲壩大江電廠以下約300 m的江段內(nèi)[8];對(duì)于產(chǎn)漂流性卵的四大家魚(青魚、草魚、鰱、鳙),其估算出來的產(chǎn)卵場位置精度達(dá)km級(jí)[9],產(chǎn)卵場的準(zhǔn)確位置及具體范圍仍未得到有效確定。綜上所述,自然水體中的魚類生態(tài)行為(如關(guān)鍵生活史等)研究需要魚類定位,但直接觀測難度較大,間接方法推求又有精度較差、準(zhǔn)確度不高等諸多問題。提高魚類定位精度、尤其是在自然水體中進(jìn)行魚類定位研究具有重要的應(yīng)用價(jià)值[10-12]。
超聲波具有方向性好,穿透能力強(qiáng),能量易于集中,在水中傳播距離較遠(yuǎn)等特點(diǎn)[13]。由于常用的電磁波信號(hào)在水中的衰減嚴(yán)重,超聲波成為目前水下信號(hào)傳播的主要載體[14]。20世紀(jì)50年代開始,超聲波技術(shù)應(yīng)用于魚類探測,典型技術(shù)有魚探儀、聲吶成像儀等[15]。與此同時(shí),采用抽樣研究的方式在測試魚體安裝超聲波信號(hào)標(biāo)記,利用水聽器進(jìn)行魚類遙測的技術(shù)也開始得到應(yīng)用[16-18]。近年來,Espinoza等學(xué)者在水下布設(shè)水聽器陣列接收標(biāo)記發(fā)出的超聲波信號(hào),通過定位算法實(shí)現(xiàn)魚類的m級(jí)精度位置捕獲[19-21],但出于技術(shù)保護(hù)原因,相關(guān)算法成果未見報(bào)道。為此,本文以目前常用的超聲波水聽器設(shè)備作為基礎(chǔ)硬件,將魚類游動(dòng)時(shí)所處水深、持續(xù)游速等作為先驗(yàn)信息,提出了一套較為完整且適用于自然水體的超聲波標(biāo)記魚m級(jí)定位算法。
在魚體安裝超聲波信號(hào)標(biāo)記,該標(biāo)記每隔一段時(shí)間會(huì)播發(fā)一組超聲波信號(hào),水聽器接收到信號(hào)后記錄接收時(shí)刻,并以此作為本文超聲波標(biāo)記魚定位算法的觀測數(shù)據(jù)。魚類定位時(shí)需布設(shè)由水聽器陣列組成的監(jiān)測網(wǎng),網(wǎng)內(nèi)水聽器間距離不宜超過其信號(hào)接收范圍。當(dāng)信號(hào)標(biāo)記魚進(jìn)入監(jiān)測網(wǎng)并被網(wǎng)內(nèi)(≥3)個(gè)水聽器同時(shí)監(jiān)測時(shí),通過記錄標(biāo)記魚的超聲波到達(dá)每個(gè)水聽器的時(shí)間TOA(time of arrival)或到達(dá)2個(gè)水聽器的時(shí)間差TDOA(time difference of arrival),測算信號(hào)標(biāo)記魚同水聽器的距離/距離差。通過多個(gè)TOA/TDOA測量值構(gòu)建關(guān)于信號(hào)標(biāo)記魚位置的雙曲線方程組,同時(shí)顧及標(biāo)記魚所處水深、持續(xù)游速等先驗(yàn)近似信息,求解方程組得到信號(hào)標(biāo)記魚的位置信息[22-24]。
在自然水體中,由于氣泡、雜質(zhì)、水流、遮擋等原因可能對(duì)水聽器接收標(biāo)記信號(hào)造成影響,并通常體現(xiàn)為如下2種情況:1)水聽器對(duì)該組超聲波信號(hào)無法有效鎖定,導(dǎo)致觀測數(shù)據(jù)缺失;2)記錄的信號(hào)觀測時(shí)刻與理論上的真實(shí)觀測時(shí)刻間存在偏差。前者可通過提升硬件性能、嚴(yán)格試驗(yàn)步驟來控制。對(duì)于第2種情況,本文在算法中進(jìn)一步采用抗差最小二乘法探測并剔除粗差觀測值,即水聽器記錄的超聲波信號(hào)接收時(shí)間存在錯(cuò)誤的這類觀測值,得到最優(yōu)的定位結(jié)果[25-26]。
設(shè)()為信號(hào)標(biāo)記的待估三維位置,(x,y,h)為第個(gè)水聽器的已知位置,第個(gè)水聽器與該信號(hào)標(biāo)記間的距離為D,m。
令為超聲波標(biāo)記的信號(hào)發(fā)射時(shí)刻,則第個(gè)水聽器對(duì)該信號(hào)的記錄時(shí)刻O存在以下關(guān)系
式中為水中聲速,m。
令D1表示該信號(hào)標(biāo)記與第個(gè)水聽器和第1個(gè)水聽器的距離差觀測值,則有
求解非線性式(3)需進(jìn)行線性化處理,因
式(4)展開:
式中K=x2+y2+h2,x,1=x-1,y,1=y-1,h,1=h-1。
假設(shè)1已知,水聽器距離差觀測值D1的精度為,m,信號(hào)標(biāo)記魚所處水深的可能范圍為,m,則觀測方程組:
其中:
對(duì)應(yīng)的觀測值權(quán)矩陣,即用來表示每一組觀測值在數(shù)據(jù)處理時(shí)所設(shè)置權(quán)重關(guān)系的矩陣為
其中為單位矩陣。
則信號(hào)標(biāo)記位置(,,)可由式(6)和式(7)按最小二乘估計(jì)得到:
將式(8)代入式(1),令=1,則得到一個(gè)關(guān)于1的二次方程,將其正根代回式(8),就得到信號(hào)標(biāo)記魚的估計(jì)位置(0,0,0),信號(hào)發(fā)射時(shí)刻的估值0可根據(jù)式(2)計(jì)算得到。在某些情況可能有2個(gè)正根,這種模糊性可通過以下先驗(yàn)信息進(jìn)行選擇:
1)1小于該水聽器的最大可觀測距離;
2)估值應(yīng)在的水深范圍內(nèi);
3)魚類在多數(shù)情況下是以低于1 m/s的持續(xù)游泳速度在水中游動(dòng)[27],當(dāng)前時(shí)刻位置估值與前一有效觀測時(shí)刻的位置間,其最大距離應(yīng)小于持續(xù)游速與2次位置結(jié)果對(duì)應(yīng)時(shí)間差的乘積。實(shí)際應(yīng)用過程中對(duì)魚持續(xù)游泳速度的設(shè)置范圍并不做限制,該參數(shù)只會(huì)影響本條先驗(yàn)信息約束的嚴(yán)格程度。
將式(2)在信號(hào)標(biāo)記魚初始位置(0,0,0)及信號(hào)發(fā)射時(shí)刻初值0處進(jìn)行Taylor展開[28],忽略二階以上分量,同時(shí)顧及標(biāo)記魚所處水深范圍等先驗(yàn)信息,則有如下觀測方程組
式中為觀測誤差矩陣。其中,
對(duì)應(yīng)的觀測值初始權(quán)矩陣與式(7)相同。
式(9)所示觀測方程組按照式(10)進(jìn)行最小二乘估計(jì),可得信號(hào)標(biāo)記魚的坐標(biāo)和信號(hào)發(fā)射時(shí)刻修正量。通過多次迭代更新初始坐標(biāo)()、信號(hào)發(fā)射時(shí)刻直至小于指定閾值,即可得到信號(hào)標(biāo)記魚的初步定位結(jié)果式(11)。
當(dāng)同一組超聲波信號(hào)被多于3個(gè)水聽器記錄時(shí),對(duì)于式(10)的最小二乘估計(jì)結(jié)果,其觀測值殘差和觀測值之間的內(nèi)符合一致性指標(biāo),即驗(yàn)后單位權(quán)中誤差,定義如下
如較水聽器距離差觀測值的精度顯著增大,則觀測值中存在粗差,此時(shí)采用抗差最小二乘確定存在粗差的觀測值。
觀測值殘差的協(xié)因數(shù)矩陣為
此時(shí),對(duì)等價(jià)權(quán)函數(shù)的選取如下
基于上述定位算法,本文針對(duì)現(xiàn)有魚類超聲波標(biāo)記1 ms級(jí)水聽器(等效距離精度1.5 m)開發(fā)了一套數(shù)據(jù)處理軟件,并在自然水體中開展試驗(yàn)分析論證本文算法的有效性。
2.1.1 測試環(huán)境
2017年9月4日在宜昌黃柏河120 m×120 m范圍內(nèi)開展測試,該水域水溫25.5 ℃,最大水深為4.0 m,水聽器處平均水壓0.3 Pa,鹽度0.0(淡水),根據(jù)Chen- Millero-Li公式計(jì)算得到超聲波在水中的傳播速度為1 498.06 m/s[31-32]。
2.1.2 測試設(shè)備
如圖1和圖2所示,在水下3 m處均勻布設(shè)由16臺(tái)Vemco VR2W和VR2C型水聽器組成的觀測網(wǎng),2種型號(hào)水聽器的觀測值精度均為1 ms,在本文測試過程中等效。靜態(tài)測試用于模擬魚休息時(shí)的狀態(tài),由于魚類超聲波信號(hào)標(biāo)記需固定在水下已知坐標(biāo)的位置,為便于安裝,本次試驗(yàn)中2個(gè)長約4 cm質(zhì)量約5 g的Vemco V9型魚類超聲波信號(hào)發(fā)射標(biāo)記分別同網(wǎng)內(nèi)2個(gè)水聽器固定在一起。動(dòng)態(tài)測試用于模擬魚游動(dòng)時(shí)的狀態(tài),船只在觀測網(wǎng)內(nèi)以0.2~1 m/s的速度航行,船底綁定2個(gè)V9型魚類超聲波標(biāo)記,船上固定PD318型北斗/GNSS接收機(jī)設(shè)備進(jìn)行cm級(jí)精度的RTK定位,以同時(shí)得到利用本文算法計(jì)算的魚類超聲波標(biāo)記水下定位結(jié)果和船只的衛(wèi)星定位結(jié)果。
圖1 測試現(xiàn)場
注:5、10、15、20、25、30 m為對(duì)指定水聽器觀測值人為設(shè)定的粗差。
2.1.3 測試過程
測試船由水聽器觀測網(wǎng)外的右上角出發(fā),迂回航行至左下角,隨后返回右上角(圖2)。測試船航行過程中,利用水聽器觀測網(wǎng)記錄本次定位測試中4個(gè)魚類超聲波標(biāo)記的信號(hào),以便模擬4條測試魚并評(píng)估對(duì)其的定位精度,即定位結(jié)果的有效性。
測試完畢后,導(dǎo)出水聽器設(shè)備記錄的各組超聲波信號(hào)接收時(shí)刻數(shù)據(jù)并利用本文算法計(jì)算4個(gè)信號(hào)標(biāo)記的定位結(jié)果,同cm級(jí)精度的北斗/GNSS RTK定位結(jié)果比較,驗(yàn)證算法的有效性。此外,如圖2所示,還人為在水聽器記錄的超聲波信號(hào)接收時(shí)刻(觀測數(shù)據(jù))中加入大小不同、數(shù)量不同的粗差,以分析不同情況下的粗差探測成功率。
2.1.4 測試算例
Vemco魚類超聲波標(biāo)記其信號(hào)頻率為69 kHz。不同標(biāo)記發(fā)射的信號(hào)如在同一時(shí)刻被同一個(gè)水聽器接收,由于信號(hào)之間會(huì)存在相互干擾導(dǎo)致水聽器無法有效識(shí)別并鎖定觀測信號(hào),這一現(xiàn)象稱之為“多用戶干擾”。因此超聲波標(biāo)記的采樣間隔被設(shè)置為在指定數(shù)值區(qū)間內(nèi)變化,以保證信號(hào)間不會(huì)出現(xiàn)長期、連續(xù)的“多用戶干擾”現(xiàn)象。4個(gè)魚類信號(hào)標(biāo)記的發(fā)射間隔從13至300 s不盡相同且存在不定期變化,同時(shí)因河面上船只經(jīng)過導(dǎo)致水流擾動(dòng)、氣泡含量增加,部分超聲波信號(hào)衰減嚴(yán)重等緣故,對(duì)4個(gè)信號(hào)標(biāo)記合計(jì)開展了115組定位測試,靜1測試數(shù)為8,靜2測試數(shù)為8,動(dòng)1測試數(shù)為89,動(dòng)2測試數(shù)為10。
采用本文提出的超聲波標(biāo)記魚定位算法計(jì)算4個(gè)標(biāo)記于各測試算例的位置信息。由式(13)計(jì)算各組有效測試算例的驗(yàn)后單位權(quán)中誤差,即水聽器觀測數(shù)據(jù)的內(nèi)符合一致性指標(biāo)均在2.2 m左右。以cm級(jí)精度的北斗/GNSS RTK定位結(jié)果為真值進(jìn)行評(píng)估,平均的三維定位精度為2.15 m,同驗(yàn)后單位權(quán)中誤差以及水聽器設(shè)備的觀測值等效精度1.5 m在一個(gè)量級(jí)。論證了基于現(xiàn)有1 ms級(jí)精度的水聽器設(shè)備,本文算法可在自然水體中獲得1倍中誤差為2.15 m精度的信號(hào)標(biāo)記魚三維游動(dòng)軌跡。
圖3 魚類信號(hào)標(biāo)記的三維定位誤差
2.2.1 存在不同大小粗差時(shí)的探測有效性
本次測試時(shí)水聽器觀測數(shù)據(jù)受環(huán)境誤差的影響相對(duì)較小,為分析更加復(fù)雜的自然水體中本文算法對(duì)粗差觀測值的抗干擾特性,人為在觀測數(shù)據(jù)中加入大小不等的粗差(圖2)。如圖4所示,當(dāng)對(duì)指定水聽器觀測數(shù)據(jù)分別加入1個(gè)5、10、20 m大小的粗差后發(fā)現(xiàn),1個(gè)5 m的粗差對(duì)單位權(quán)中誤差的影響較為有限;當(dāng)粗差≥10 m時(shí),可通過單位權(quán)中誤差判定水聽器觀測值中是否存在粗差,且該探測效果會(huì)隨著粗差的增大而顯著提升。
圖4 實(shí)測數(shù)據(jù)的單位權(quán)中誤差(人為加入1個(gè)粗差)
2.2.2 存在不同數(shù)量粗差時(shí)的探測有效性
在自然水體中,可能存在粗差觀測值個(gè)數(shù)、粗差大小不盡相同等工況。為此如圖2所示,對(duì)4個(gè)信號(hào)標(biāo)記的每一組有效觀測算例人為加入了1~5個(gè)粗差,5個(gè)粗差對(duì)應(yīng)的大小依次為10、15、20、25、30 m,以驗(yàn)證本文方法在不同粗差觀測條件下的抗干擾性。根據(jù)式(15)中0、1的設(shè)置范圍及其實(shí)測有效性分析,采用0=1.0,1=2.4進(jìn)行粗差探測。如圖5的統(tǒng)計(jì)結(jié)果所示,4個(gè)信號(hào)標(biāo)記的粗差探測成功率分布情況基本一致,粗差探測成功率隨著粗差個(gè)數(shù)增加而下降。當(dāng)僅存在1個(gè)粗差觀測值時(shí),對(duì)于總計(jì)115個(gè)測試算例,其粗差準(zhǔn)確探測的成功率高達(dá)100.0%;存在3個(gè)粗差觀測值時(shí),粗差準(zhǔn)確探測的成功率仍高達(dá)84.3%;3個(gè)以上粗差時(shí)成功率明顯下降,當(dāng)粗差個(gè)數(shù)大于5個(gè),即粗差觀測值個(gè)數(shù)占觀測值總數(shù)的比例大于31.25%時(shí),本文算法能探測出觀測數(shù)據(jù)中存在粗差,但無法有效確定粗差觀測值。
圖5 不同超聲波標(biāo)記魚在含有不同比例粗差觀測值情況下其粗差探測成功率
本文提出了一套適用于自然水體的超聲波標(biāo)記魚定位算法并在宜昌黃柏河進(jìn)行了實(shí)測分析?;诔S玫? ms級(jí)觀測精度(等效距離精度為1.5 m)的水聽器布設(shè)觀測網(wǎng),本算法可得到魚類超聲波標(biāo)記優(yōu)于2.15 m精度的水下三維位置。除此之外,測試還人為引入了自然水體可能產(chǎn)生的不同粗差量級(jí)及個(gè)數(shù),探討了本文算法在各類粗差工況下的探測成功率和抗干擾性:量級(jí)方面,本算法可接近100%探測出大于10 m量級(jí)的粗差觀測值;3個(gè)以內(nèi)(即粗差觀測值個(gè)數(shù)占觀測值總數(shù)的比例小于18.75%)的粗差觀測值探測成功率較高(可達(dá)84.3%以上),3個(gè)以上時(shí)粗差探測成功率明顯下降,5個(gè)及以上,即粗差觀測值占比大于31.25%時(shí),則基本只能探測出觀測數(shù)據(jù)中存在粗差而無法有效確定粗差值。
本文提出的超聲波標(biāo)記魚定位算法,為自然水體中確定魚體精確游動(dòng)軌跡提供了一種有效的解決方案,并充分考慮自然水體的復(fù)雜性,測試了算法粗差探測有效性和抗干擾性,為算法的實(shí)際應(yīng)用提供定量指導(dǎo)。在今后實(shí)踐過程中,隨著水聽器設(shè)備觀測精度的提升,設(shè)備在水中的位置穩(wěn)定性等試驗(yàn)條件的嚴(yán)格控制,以及采用信號(hào)標(biāo)記中壓力傳感器對(duì)水深數(shù)據(jù)的精化,按照本文算法預(yù)計(jì)能得到更加精確可靠的標(biāo)記魚三維位置。此外,通過完善數(shù)據(jù)通訊接口,本文提出的相關(guān)算法可有效應(yīng)用于不同廠家的魚類超聲波標(biāo)記定位設(shè)備。本文的研究成果現(xiàn)已有效應(yīng)用于南海海上人工魚礁投礁效果評(píng)估以及高要江段鯉魚繁殖期運(yùn)動(dòng)行為研究,未來對(duì)漁業(yè)增殖、魚類棲息地保護(hù)、魚類洄游通道等研究均具有一定的推動(dòng)作用。
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Accurate determination algorithm of swimming trajectory for ultrasonically-tagged fish in natural water
Hou Yiqun1,2, Zou Xuan1,3, Jiang Wei1※, Chen Liang4, Zhu Jiazhi1
(1.443100; 2.,430079,;3.430079,; 4.200438,)
An important goal of hydrobiology is the simulation, reconstruction and restoration of important fish habitats, in which fish species form aquatic ecosystems’ climax communities, enabling structural and functional restoration of river ecosystems. Traditional methods for identifying key fish habitat locations such as spawning grounds, include fish resource surveys, observation of fish spawning behavior and interviews with fishermen. But these are subject to problems including poor accuracy and large error. Precise positioning of fish can accurately locate key habitats (such as spawning grounds) based on key life cycle phases (such as spawning periods), permitting observation of corresponding habitat parameters. Fish movement trajectory data can also deepen understanding of fish habits and habitats, permitting suitable habitat indicators to be scientifically determined, and providing theoretical and technical support for fish protection and habitat restoration efforts. Ultrasonic tag tracking technology is widely used in fish behavior research due to its long underwater propagation distance and broad applicability. But most existing researches derived fish movement trajectories from hydrophone data using equipment manufacturers’ software or services, and few articles concerning fish positioning principles and methods optimized for natural aquatic environments have been published. The Chan’s algorithm (1994) in literature[24] and robust least squares estimation were combined to get the location of ultrasonically-tagged fish in this paper, leveraging the strengths of these methods to overcome their disadvantages when used singly. Chan’s algorithm was first used to obtain approximate coordinates of fish, which were used as initial position estimates from which the final position estimates were obtained with robust least squares. Prior information such as water depth and fish swimming speed could also be taken into account, making the proposed positioning method well-suited for dealing with ultrasonically-tagged fish in natural aquatic environments. The proposed method was suitable for existing ultrasound hydrophones, and effectively solved problems with large observation errors. Based on these research results, the UWP (under water positioning) software package was developed. To verify the effectiveness of the proposed method, an observation network was constructed which consisting of 16 hydrophones uniformly distributed over a area of 120 m×120 m in Huangbai River, Yichang. 4 ultrasonic signal tags were used to evaluate the positioning results, 2 was co-located with hydrophones for static simulation, and the other 2 affixed to a boat hull for dynamic simulation. Comparisons with Beidou/GNSS RTK with centimeter-level accuracy positioning estimates over 115 groups of test results, using millisecond-level accuracy observation data from existing hydrophones, swimming trajectories of ultrasonically-tagged fish could be obtained to an accuracy of about 2.15 m. While complex water environments degraded this accuracy, where single observations contained gross errors exceeding 10 m, 100% of these errors could be identified. The success rate for identification of observations with gross error was a gradually declining function of gross errors, dropping to 84.3% for 3 such observations. With over 3 gross error-bearing observations, the success rate declined significantly. With over 5 gross error-bearing observations where gross error-bearing observations accounted for over 31.25% of all observations, application of the proposed method could detect the error’ existence, but was unable to identify the error-bearing observations effectively. The ultrasonic tag precise positioning method of fish proposed in this paper provide an effective method for determining the accurate swimming trajectory of fish in rivers, lakes and seas with low visibility. In addition, by modifying the data communication interface, this method can be effectively applied to ultrasonicall-taggeds fish and hydrophones of different manufacturers. In the future, it can play a more important role in promoting ecological environmental protection, and human beings’ understanding of ecological and behavioral evolution in the aquatic environment at the population level.
position measurement; ultrasonic waves; algorithms; fish; natural aquatic environment; distance intersection; swimming trajectory; gross error detection
侯軼群,鄒 璇,姜 偉,陳 亮,朱佳志.自然水體中超聲波標(biāo)記魚游動(dòng)軌跡精密確定算法[J]. 農(nóng)業(yè)工程學(xué)報(bào),2019,35(3):182-188.doi:10.11975/j.issn.1002-6819.2019.03.023 http://www.tcsae.org
Hou Yiqun, Zou Xuan, Jiang Wei, Chen Liang, Zhu Jiazhi. Accurate determination algorithm of swimming trajectory for ultrasonically-tagged fish in natural water[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(3): 182-188. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2019.03.023 http://www.tcsae.org
2018-09-12
2018-12-31
三峽工程魚類資源保護(hù)湖北省重點(diǎn)實(shí)驗(yàn)室開放課題項(xiàng)目(SXSN/4008);國家自然科學(xué)基金資助項(xiàng)目(51609157,51609155)
侯軼群,助理研究員,主要從事魚類生態(tài)學(xué)、生態(tài)水力學(xué)等研究。Email:greenhan16@163.com
姜 偉,博士,高級(jí)工程師,主要從事鱘魚繁殖技術(shù)、長江生態(tài)修復(fù)研究。Email:jiang_wei6@ctg.com.cn
10.11975/j.issn.1002-6819.2019.03.023
TB568
A
1002-6819(2019)-03-0182-07