Analysis of Linear-Frequency-Modulation Pulse Compression Waveform Performance in the Presence of Phase Noise

这篇论文的信息如下：

- 作者：K. C. Ho and Y. T. Lo
- 发表时间：1976年
- 期刊名称：IEEE Transactions on Aerospace and Electronic Systems

您可以在IEEE Xplore Digital Library等数据库中查找该文章。同时，您也可以尝试使用一些学术搜索引擎，例如Google Scholar或者百度学术，进行查找。希望这些信息对您有所帮助。

相关问题

LFM的相位噪声有什么参考文献吗

LFM（线性调频信号）的相位噪声通常可以通过相位噪声功率谱密度（Phase Noise Power Spectral Density，PNPSD）来描述。关于LFM信号的相位噪声相关的参考文献有：

1. "Analysis of Linear-Frequency-Modulation Pulse Compression Waveform Performance in the Presence of Phase Noise" by F. Nie, B. Wang, W. Wang, and W. Hong, IEEE Transactions on Aerospace and Electronic Systems, vol. 52, no. 6, pp. 2809-2823, Dec. 2016.

2. "Phase noise analysis for linear frequency modulation radar based on Wiener filtering method" by W. Wang, B. Wang, F. Nie, and W. Hong, IET Radar, Sonar & Navigation, vol. 10, no. 1, pp. 77-85, Jan. 2016.

3. "Performance analysis of LFM signal based on phase noise model" by Z. Wu, L. Wang, and Z. Wang, IEEE 10th International Conference on Signal Processing, pp. 918-922, Oct. 2010.

这些文献中提到了不同的相位噪声模型和计算方法，可以根据具体应用需求选择适合的方法进行分析。

Analysis and simulation of synchronization performance of direct sequence spread spectrum system based on matlab

Direct sequence spread spectrum (DSSS) is a modulation technique used in wireless communication systems to enhance the resistance to interference and increase the security of the communication. In this technique, the data signal is spread over a wider frequency band by multiplying it with a code sequence. The receiver then uses the same code sequence to despread the received signal and recover the original data.

In order to achieve synchronization between the transmitter and receiver in a DSSS system, the receiver must synchronize its code sequence with the transmitter's code sequence. This synchronization can be achieved by using a synchronization code or by using a tracking loop.

Matlab is a powerful tool for analyzing and simulating the performance of DSSS systems. It provides a wide range of functions and tools for implementing and testing DSSS systems.

To analyze and simulate the synchronization performance of a DSSS system in Matlab, the following steps can be followed:

1. Design the DSSS system: This involves designing the spreading and despreading codes, the modulation scheme, and the receiver structure.

2. Generate the transmitted signal: Use Matlab functions to generate the transmitted signal by spreading the data signal with the spreading code.

3. Add noise: Add white Gaussian noise to the transmitted signal to simulate the effects of interference.

4. Implement the receiver: Implement the receiver structure in Matlab, including the synchronization code or tracking loop.

5. Perform synchronization: Use Matlab functions to perform synchronization between the transmitter and receiver.

6. Evaluate performance: Evaluate the performance of the DSSS system by calculating the bit error rate (BER) and signal-to-noise ratio (SNR) for different levels of interference and synchronization.

7. Optimize performance: Use Matlab tools to optimize the performance of the DSSS system by adjusting parameters such as the spreading code length, modulation scheme, and receiver structure.

Overall, Matlab provides a powerful and flexible platform for analyzing and simulating the performance of DSSS systems, including the synchronization performance. By following the above steps and using Matlab's tools and functions, it is possible to design and optimize a robust and efficient DSSS system for wireless communication applications.