Research On The Key Techniques Of Hf Signal Monitoring And System Implementation

Electromagnetic spectrum monitoring is basis of spectrum supervision and prerequisite to get information in non-cooperative communication, the primary task of which is to search for signals emitted by counterpart and measure parameters. Applications of new technologies and frameworks result in high frequency(HF) channel environment more complicated, and lead to challenge of monitoring. This paper studies three key technologies in HF signal monitoring system, which is automatic signal search, frequency-hopping(FH) signal detection, as well as burst signal capture and detection. The relevant algorithms have also been realized on HF signal processing platform. The main work can be summarized as follows:1. Based on the simulation of Watterson model, this paper analyzes influences of some complicated and time-varying factors on the HF signals. Morphological theory has been investigated to pre-process on signal search and detection.2. The paper studies common methods of signal search. Four chief points in the process of signal search are discussed in detail, which is power spectrum estimation, detection threshold, energy detection and parameter measurement, as well as signal collection update. With regard to colored noise and multi-spectral peak signals, a new signal reconnaissance method based on morphology pre-processing is proposed in this paper. Simulation results show that colored noise can be suppressed, as well as weak signals and multi-spectral peak signals reliably detected in a given complicated HF channel environment.3. Time-frequency(TF) detection basic principles are researched. The cruxes in the process of TF detection have been examined and the most significant ones are spectrogram estimation, pre-processing of detection, feature extraction and detection in TF domain. Aiming at the difference TF distribution between FH signals, interferences and noises in HF channel, a novel TF detection algorithm based on morphology pre-processing is proposed to suppress interferences and noises. It can detect FH signal on the condition that we know the range of hopping period. Finally, synthesized information entropy is employed to evaluate the performance of the algorithm. Simulation results show that the algorithm is effective.4. Capture and detection of burst signals have been investigated. A multichannel method based on Goertzel algorithm has been exploited to capture burst signals quickly. After researching on the three methods for burst signal presence detection, the dual sliding window algorithm is improved for end-time extraction. Taking performance and efficiency into account synthetically, this paper designs a scheme of burst signals capture and detection which employs the aforementioned three algorithms on the condition of different SNRs.5. The HF signal monitoring system has been preliminary implemented. The testing results show that the system is pragmatic and the efficiency of the proposed algorithm is confirmed.