Dissertation > Excellent graduate degree dissertation topics show

Research on Signal Modulation Recognition and Parameter Estimation of OTH Ground Wave Radar

Author: ShaMingHui
Tutor: YuanYeShu
School: Harbin Institute of Technology
Course: Information and Communication Engineering
Keywords: feature extraction modulation recognition parameters estamation instantaneous frequency time-frequency analysis
CLC: TN957.51
Type: Master's thesis
Year: 2010
Downloads: 80
Quote: 1
Read: Download Dissertation

Abstract


Radar signal recognition technology is an important research in the field of electronic reconnaissance and countermeasures. In this paper, LFM and BPSK, commonly used in high frequency ground wave radar, are analyzed and recognized. Modulation pattern identification and parameter estimation are simulated under the Gaussian white noise background.Firstly, LFM and BPSK, commonly used in HF ground wave radar, are introduced and analyzed their time and frequency features. In order to distinguish the modulation pattern and parameter of radar signal and recognize the radar signal effectively, the features of different radar signal must be analyzed to get the characteristic that can reflect the difference, which is called feature extraction. In this article, from the view of intrapulse modulation characteristics, the features of instantaneous frequency and time-frequency distribution are analyzed, the different features of different signals are extracted. On the basis of the extracted features, the instantaneous frequency of different radar signals are distilled based on instant autocorrelation method and phase frequency measuring method, and time-frequency distributions are extracted by STFT, WVD method respectively. Based on the characteristics of instantaneous frequency and time-frequency distributions respectively, modulation pattern identification and parameter estimation of the HF ground wave radar are studied. Different modulation patterns of radar signal are identified, and the recognition probabilities are analyzed under different signal-noise ratio. The parameters of different radar signals are extracted, and the extraction accuracies are analyzed under different signal-noise ratio. his paper proposes a combination of short-term Fourier transform and wavelet transform the two-phase pulse coded signal analysis algorithms, the simulation of the two-phase pulse code modulation parameters from real-time performance has improved significantly. To the linear frequency modulation signal, mainly to a transformation, Radon-Ambiguity transform an analysis of noise in different circumstances of the simulation, the various methods of calculation error and also an analysis of results showed that Radon-Ambiguity is a precision, A small amount of calculation method of calculation. Next on the radar pulse width, repeated intervals, such as time-domain parameters extraction methods were studied. The time domain parameter’s extraction has used based on the instantaneous autocorrelation radar time domain parameter extraction algorithm, may obtain the very high pulse parameter measuring accuracy, the algorithm is simple, and the operand is not big. This research is worked under the circumstances of single carrier and additive white Gaussian noise, so the study is only applied to some simple situations. The situations of multi-carrier, non-additive white Gaussian noise or colored noise, are the further work of HF ground wave radar signal recognition research.

Related Dissertations

  1. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  2. Research on Ionosphere Contamination of High Frequency Radar Echoes and Time-Frequency Analysis Technology,TN958.93
  3. The Research on Ship Imaging Algorithm under the Sea Clutter Background,TN958
  4. ISAR Imaging Simulation of Space Targets and Target Recognition Based on ISAR Images,TN957.52
  5. Research on Feature Extraction and Classification of Pulse Waveform for Cholecystitis and Nephrotic Syndrome Diagnosis,TP391.41
  6. Application of Q-Learning in the Content-Based Image Retrieval Technology,TP391.41
  7. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  8. Research on Automatic Picking of First Arrival Based on Wavelet Transform,TP311.52
  9. Band Entropy Method and Its Application to Fault Diagnosis of Rolling Bearings,TH165.3
  10. Broadband instantaneous frequency measurement receiver RF front-end research,TN957.5
  11. Image feature extraction based image fusion research,TP391.41
  12. Time-frequency analysis of the application of the RCS test method,TN953
  13. The Car Insurance Customer of People’s Insurance Company of China Risk Assessment Modeling Research and Application,O211.67
  14. View-based 3D model retrieval technology,TP391.41
  15. Intelligent mobile robot map description and navigation methods,TP242.6
  16. Natural classroom face recognition system based on video streaming Research and Implementation,TP391.41
  17. Based on PCA and SVM automotive coating line electromechanical equipment intelligent diagnosis,TH165.3
  18. Based on spectral regularization of linear dimensionality reduction methods,TP391.41
  19. Automatic Target Recognition fluorescent magnetic particle inspection image processing techniques,TP391.41
  20. Crystal wafer automatic sorting technology research,TP274
  21. Handwritten Character Recognition feature extraction and classification research,TP391.41

CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radar > Radar equipment,radar > Radar receiving equipment > Radar signal detection and processing
© 2012 www.DissertationTopic.Net  Mobile