Àâòîð: Ùåðáîâ È.Ë.
Íàçâàíèå: Àëãîðèòì àäàïòèâíîãî íåëèíåéíîãî ñãëàæèâàíèÿ äàííûõ ìíîãîïàðàìåòðè÷åñêèõ èçìåðåíèé
Âûïóñê: 113
Ðóáðèêà: Ñèñòåìíûé àíàëèç
Ãîä: 2025
Áèáëèîãðàôèÿ: Ùåðáîâ È.Ë. Àëãîðèòì àäàïòèâíîãî íåëèíåéíîãî ñãëàæèâàíèÿ äàííûõ ìíîãîïàðàìåòðè÷åñêèõ èçìåðåíèé // Óïðàâëåíèå áîëüøèìè ñèñòåìàìè. - 2025. - Âûï. 113. - Ñ.37-57.
Êëþ÷åâûå ñëîâà: àëãîðèòì àäàïòèâíîãî íåëèíåéíîãî ñãëàæèâàíèÿ, ñãëàæèâàþùèé ïîëèíîì, âåêòîð êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà, ëèíåéíî íåçàâèñèìûå áàçèñíûå ôóíêöèè, ?-îðòîãîíàëüíûå áàçèñíûå ôóíêöèè
Êëþ÷åâûå ñëîâà (àíãë.): adaptive nonlinear smoothing algorithm, smoothing polynomial, vector of coefficients of the smoothing polynomial, linearly independent basis functions, ?-orthogonal basis functions
Àííîòàöèÿ: Ðàññìîòðåíà ðàáîòà àëãîðèòìà àäàïòèâíîãî íåëèíåéíîãî ñãëàæèâàíèÿ äàííûõ ìíîãîïàðàìåòðè÷åñêèõ èçìåðåíèé. Ðàçðàáîòàííûé àëãîðèòì îñóùåñòâëÿåò ñîâìåñòíóþ îáðàáîòêó äàííûõ èçìåðåíèé, îáëàäàþùèõ ïðîñòðàíñòâåííîé è âðåìåííîé èçáûòî÷íîñòüþ. Äëÿ ïîëó÷åíèÿ íåçàâèñèìûõ îöåíîê âåêòîðà êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà â ðàáîòå àëãîðèòìà èñïîëüçóþòñÿ ñòðóêòóðû ëèíåéíî íåçàâèñèìûõ è ?-îðòîãîíàëüíûõ áàçèñíûõ ôóíêöèé, îñóùåñòâëÿþùèå ñîâìåñòíóþ îáðàáîòêó ðàçëè÷íûõ òèïîâ èçìåðÿåìûõ ïåðâè÷íûõ êîîðäèíàò ìåñòîïîëîæåíèÿ èñïûòûâàåìûõ îáúåêòîâ, ïîëó÷åííûõ îò âíåøíåòðàåêòîðíûõ èçìåðèòåëüíûõ ñðåäñòâ. Äëÿ íà÷àëà èòåðàòèâíîãî ïðîöåññà íàõîæäåíèÿ ìàêñèìàëüíî äîñòîâåðíîãî çíà÷åíèÿ âåêòîðà êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà íà ïåðâîì øàãå ñãëàæèâàíèÿ ïðåäëîæåí ñïîñîá âûáîðà íà÷àëüíîãî ïðèáëèæåíèÿ âåêòîðà êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà, êîòîðûé äëÿ êàæäîãî ïîñëåäóþùåãî øàãà ëîêàëüíî-ñêîëüçÿùåãî ñãëàæèâàíèÿ äàííûõ èçìåðåíèé ïîçâîëÿåò èñïîëüçîâàòü çíà÷åíèå, êîòîðîå áûëî ïîëó÷åíî íà ïðåäûäóùåì øàãå ñãëàæèâàíèÿ. Ïðèìåíåííûå â ðàáîòå àëãîðèòìà ìåòîäèêè ïðîâåðêè çíà÷èìîñòè êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà ïîçâîëèëè îïòèìèçèðîâàòü ïðîöåññ îïðåäåëåíèÿ çíà÷èìûõ êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà. Ïðèìåíåíèå ðàçðàáîòàííîãî ñïîñîáà âûáîðà íà÷àëüíîãî ïðèáëèæåíèÿ âåêòîðà êîýôôèöèåíòîâ ñãëàæèâàþùåãî ïîëèíîìà è ïðåäëîæåííûõ ìåòîäèê ïîçâîëèëî óìåíüøèòü âðåìÿ íà îáðàáîòêó äàííûõ òðàåêòîðíûõ èçìåðåíèé. Ïî ðåçóëüòàòàì ïðîâåäåííîãî ýêñïåðèìåíòàëüíîãî èññëåäîâàíèÿ óñòàíîâëåíî, ÷òî ðàçðàáîòàííûé àëãîðèòì àäàïòèâíîãî íåëèíåéíîãî ñãëàæèâàíèÿ äàííûõ ìíîãîïàðàìåòðè÷åñêèõ òðàåêòîðíûõ èçìåðåíèé ïîâûøàåò òî÷íîñòü è äîñòîâåðíîñòü îïðåäåëåíèÿ âòîðè÷íûõ êîîðäèíàò ïðîñòðàíñòâåííîãî ïîëîæåíèÿ ËÀ â òðàåêòîðíûõ èçìåðèòåëüíî-âû÷èñëèòåëüíûõ êîìïëåêñàõ è îáåñïå÷èâàåò óñòîé÷èâîñòü â ðàáîòå ïðè îáðàáîòêå äàííûõ èçìåðåíèé ñî ñáîÿìè è ãðóáûìè îøèáêàìè èçìåðåíèé.
Àííîòàöèÿ (àíãë.): The paper considers the operation of an adaptive nonlinear smoothing algorithm for multiparameter measurement data. This algorithm allows for the joint processing of measurement data with spatial and temporal redundancy, which improves the accuracy and reliability of determining the secondary parameters of the test objects' positions. The algorithm uses structures of linearly independent and ?-orthogonal basis functions, which allow for the joint processing of various types of measured primary coordinates of the test objects' positions obtained from external trajectory measuring instruments, to obtain independent estimates of the smoothing polynomial coefficient vector. The proposed method for selecting the initial approximation of the smoothing polynomial coefficient vector to begin the iterative process of finding the most reliable value of the smoothing polynomial coefficient vector at the first smoothing step allows for each subsequent step of locally moving smoothing of the measurement data to use the value obtained at the previous step of locally moving smoothing. The applied in the work algorithm methods of checking the significance of the coefficients of the smoothing polynomial, allowed to optimize the process of determining the significant coefficients of the smoothing polynomial. The application of the developed method of selecting the initial approximation of the vector of coefficients of the smoothing polynomial and the proposed methods allowed to reduce the time for processing the data of trajectory measurements. According to the results of the conducted experimental study it was established that the developed algorithm of adaptive nonlinear smoothing of data of multiparameter trajectory measurements increases the accuracy and reliability of determining the secondary coordinates of the spatial position of the aircraft in trajectory measuring and computing complexes and ensures stability in operation when processing measurement data with failures and gross measurement errors.
â ôîðìàòå PDF
Ïðîñìîòðîâ: 572, çàãðóçîê: 219, çà ìåñÿö: 12.
Íàçàä