直擴信號偵察的關(guān)鍵技術(shù)研究

發(fā)布時間：2018-10-24 21:50

【摘要】：由于擴頻通信具有展寬頻帶、檢測概率低、抗干擾能力強等優(yōu)良特點,使得擴頻通信在軍事和民用上都得到了廣泛的應(yīng)用。而其中直接序列擴頻通信是擴頻通信系統(tǒng)中比較常用的一種擴頻通信方式。對于直擴信號偵察,首先要對直擴信號的存在進行檢測,然后估計出直擴信號的載頻、偽碼周期、碼速率以及偽碼序列等重要參數(shù),以便能夠獲取原始的信息碼或者對其進行各種干擾。在針對信號檢測以及對直擴通信的參數(shù)估計上面,本文主要研究了平方倍頻法、延時相乘檢測算法、循環(huán)譜切片法、以及相關(guān)二階矩和二次功率譜法等算法來檢測直接序列擴頻信號的存在時,并估計出了直擴信號的載頻(平方倍頻法、循環(huán)譜切片法)、偽碼碼速率(延時相乘算法、循環(huán)譜切片法)、偽碼周期(相關(guān)二階矩、二次功率譜法),針對不同算法,在驗證了算法對于參數(shù)估計和檢測的有效性的基礎(chǔ)上,然后進行了性能分析。在偽碼序列估計問題上,采用了最大似然估計法和小波神經(jīng)網(wǎng)絡(luò)兩種算法。針對最大似然估計方法,利用迭代的思想,大大簡化了最大似然估計的計算過程。而在利用神經(jīng)網(wǎng)絡(luò)估計偽碼序列時,利用小波神經(jīng)元來改進了傳統(tǒng)的神經(jīng)網(wǎng)絡(luò),加強了神經(jīng)網(wǎng)絡(luò)的抗噪聲性能,使得在低信噪比條件下,偽碼的估計性能得到了提高。最后對于周期長碼直擴信號,借鑒短碼估計的知識,采用了一種分段的最大似然估計算法來估計偽碼序列,并對算法的的功能進行了驗證和性能分析。
[Abstract]:Spread spectrum communication has been widely used in both military and civil fields because of its advantages such as wide bandwidth, low detection probability and strong anti-jamming ability. Direct sequence spread spectrum communication is a common spread spectrum communication mode in spread spectrum communication system. For the detection of DSSS signals, the existence of DSSS signals is first detected, and then the carrier frequency, pseudo-code period, code rate and pseudo-code sequence of DSSS signals are estimated. In order to obtain the original information code or interfere with it. On the basis of signal detection and parameter estimation of DSSS communication, this paper mainly studies the squared frequency doubling method, the delay multiplication detection algorithm, the cyclic spectrum slice method. When detecting the existence of direct sequence spread spectrum signal by correlation second-order moment and quadratic power spectrum method, the carrier frequency (squared doubling method, cyclic spectrum slice method) and pseudo-code rate (delay multiplication algorithm) of direct sequence spread spectrum signal are estimated. Cyclic spectrum slicing method, pseudo-code period (correlation second-order moment, quadratic power spectrum method), for different algorithms, the effectiveness of the algorithm for parameter estimation and detection is verified, and then the performance analysis is carried out. In the problem of pseudo code sequence estimation, two algorithms, maximum likelihood estimation and wavelet neural network, are used. For the maximum likelihood estimation method, the calculation process of the maximum likelihood estimation is greatly simplified by using iterative method. When using neural network to estimate pseudo-code sequence, wavelet neural network is used to improve the traditional neural network, and the anti-noise performance of neural network is enhanced, so that the estimation performance of pseudo-code is improved under the condition of low signal-to-noise ratio (SNR). Finally, a piecewise maximum likelihood estimation algorithm is used to estimate the pseudo code sequence for the period long code DSSS signal, and the function of the algorithm is verified and its performance is analyzed.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN914.42

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