Finally this dissertation expatiating on hardware and software designs of the dissipation factor calculating module . the hardware design including the collection of supervising signals , the choice of the disposing cmos chip and their electro circuit schematics 最后對介損監(jiān)測計算模塊的軟硬件模塊進行了設(shè)計。硬件設(shè)計包括監(jiān)測信號的采集、參數(shù)計算處理模塊dsp芯片選型和硬件電路設(shè)計。
The potential applications of amr include both civil and military communication , especially non - cooperative communications and communication confrontation , such as identifying signals , supervising signals , distinguishing interference , electronic confrontation , analyzing military threat , etc . on the basis of our analysis to the existing research on feature abstraction , the related feature abstraction methods are optimized in this paper , resulting several effective methods such as the feature abstraction based on transformation domain , stepped voltage level analysis , normalized carrier - free spectral energy analysis , squared signal and fourth powered signal analysis , etc . both the decision theory based on recognition algorithms and the artificial neural network ( ann ) based on recognition algorithms is analyzed , and the former is selected as it is more appropriate for this research 調(diào)制類型的自動識別廣泛應(yīng)用于民用通信與軍用通信,尤其是對于非合作性通信、通信對抗,比如:信號確認(rèn)、信號監(jiān)控、干擾辨識、電子對抗、軟件無線電、電子救援、通信對抗、軍事威脅分析等。本論文在分析現(xiàn)有研究的基礎(chǔ)上,借鑒了已有的特征提取方法,對相關(guān)調(diào)制類型特征提取方法進行了優(yōu)化,使用了一些有效的方法,如基于變換域特征提取方法、梯層電平分析方法、剔除載波后的歸一化頻域能量分析方法、信號平方后的頻譜分析方法、信號四次方后的頻譜分析方法等。通過對基于決策理論和基于人工神經(jīng)網(wǎng)絡(luò)兩種識別算法進行分析,本論文選擇了較適合的基于決策理論的識別算法。