According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the ...According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the phase of Pseudo-Noise-code(PN-code),Doppler frequency and its rate-of-change is presented to achieve high sensitivity in sensing high-frequency dynamics. By eliminating the correlation peak loss caused by ultrahigh Doppler frequency and its rate-of-change offset,the proposed method improves the acquisition sensitivity by increasing the non-coherent accumulation time. The validity of the algorithm is proved by theoretical analysis and simulation results. It is shown that signals with a carrier- to-noise ratio as low as 39 dBHz can be captured with high performance when the Doppler frequency is up to ±1 MHz and its rate-of-change is up to ±200 kHz/s.展开更多
Serveral methods for the pararrel acquisition of a PN sequence in a baseband direct sequence spread spectrum system are investigated. Four different kinds of schemes are considered: the optimal estimation scheme, the ...Serveral methods for the pararrel acquisition of a PN sequence in a baseband direct sequence spread spectrum system are investigated. Four different kinds of schemes are considered: the optimal estimation scheme, the locally optimal estimation scheme, the optimal testing searches and the locally optimal testing scheme. In the four kinds of parallel acquisition schemes, the expressions for the probability of error are given and compared with the actual error probabilities obtained via Monte Carlo simulation. We also outline a technique that can be suboptimal because of a large amount of hardware and computation when using the parallel acquisition schemes.展开更多
Aiming at improving acquisition performance for direct sequence spread spectrum （DSSS） signals, a new acquisition algorithm based on fast Fourier transform （FFT） is proposed. The code phases are parallel searched ...Aiming at improving acquisition performance for direct sequence spread spectrum （DSSS） signals, a new acquisition algorithm based on fast Fourier transform （FFT） is proposed. The code phases are parallel searched throughout the Doppler frequency domain. Since the influence of Doppler frequency errors on peak-to- average ratios of correlation power shows a pattern similar to the sinc function, it is our belief that by judging on peak-to-average ratios for different Doppler frequency errors false alarm probabilities should be lowered. Analyses have supported the underlying principle of this new algorithm. Simulation results have also indicated that the new algorithm can effectively improve the acquisition performance for DSSS signals.展开更多
An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a s...An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.展开更多
In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and ...In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.展开更多
基金supported by the Youth Science Fund,National Natural Science Foundation of China under Grant No.61102130
文摘According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the phase of Pseudo-Noise-code(PN-code),Doppler frequency and its rate-of-change is presented to achieve high sensitivity in sensing high-frequency dynamics. By eliminating the correlation peak loss caused by ultrahigh Doppler frequency and its rate-of-change offset,the proposed method improves the acquisition sensitivity by increasing the non-coherent accumulation time. The validity of the algorithm is proved by theoretical analysis and simulation results. It is shown that signals with a carrier- to-noise ratio as low as 39 dBHz can be captured with high performance when the Doppler frequency is up to ±1 MHz and its rate-of-change is up to ±200 kHz/s.
文摘Serveral methods for the pararrel acquisition of a PN sequence in a baseband direct sequence spread spectrum system are investigated. Four different kinds of schemes are considered: the optimal estimation scheme, the locally optimal estimation scheme, the optimal testing searches and the locally optimal testing scheme. In the four kinds of parallel acquisition schemes, the expressions for the probability of error are given and compared with the actual error probabilities obtained via Monte Carlo simulation. We also outline a technique that can be suboptimal because of a large amount of hardware and computation when using the parallel acquisition schemes.
基金Sponsored by the National "863" Program Project (1010021310XXX)
文摘Aiming at improving acquisition performance for direct sequence spread spectrum （DSSS） signals, a new acquisition algorithm based on fast Fourier transform （FFT） is proposed. The code phases are parallel searched throughout the Doppler frequency domain. Since the influence of Doppler frequency errors on peak-to- average ratios of correlation power shows a pattern similar to the sinc function, it is our belief that by judging on peak-to-average ratios for different Doppler frequency errors false alarm probabilities should be lowered. Analyses have supported the underlying principle of this new algorithm. Simulation results have also indicated that the new algorithm can effectively improve the acquisition performance for DSSS signals.
基金supported by the National Natural Science Foundation of China under Grant No.61271168
文摘An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.
文摘In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.
