The Signal Separation And Detection For Wide-band Reconnaissance In High Frequency

With the ability of achieving long distance communication by relative low power, high frequency communication has become an important technology in communication domain and has a wide application in military communication,weather forecast,business,diplomacy etc for many years. Signal reconnaissance in high frequency is an important means of collecting and obtaining modern intelligence. Narrow-band reconnaissance is faced with great challenge with the development of modern electronic information technology, such as auto-adaption communication,spread communication,burst communication etc. In order to adapt the new changes in high frequency communication, wide-band reconnaissance will surely become the development trend.At present, the main mode of wide-band reconnaissance in high frequency is human surveillance, which requires operators to keep watching the monitor displayed with the wide-band time-frequency information. Because of the better concealment of the low intercepting signals and the influence of spreading characteristic in high frequency channels, human surveillance can not meet the requirement of the reconnaissance of high speed signal,wide-band signal,short-time signal,burst signal. So we need to study the signal auto- separation and detection.Based on the theory of wide-band receiving, this dissertation study the time-frequency characteristic of signal through the time-frequency analysis of wide-band signal, then the corresponding algorithms are presented, which realizes the auto-separation and detection of wide-band signals in high frequency in complex environment .The main work of this dissertation are summarized as below:Firstly, this paper deals with how to select the tools for time-frequency analysis and discusses the theory of signal detection and processing, thus laying a theory foundation for signal detection and processing based on time-frequency analysis of the signal rather than based on channel digitalization with the bank of filters.Secondly, in order to meet the different requirements on the estimation of the background noise within wide-band spectrum based on time-frequency analysis, four methods are presented: The Throw Big and Keep Small Method, The Logarithm Statistics Method, The Shift Frequency Mean Method, The Time Frequency Mean Method, all of these methods are adaptable and robust, atmospherics interference can also be detected when the background noise is estimated.Thirdly, based on the distribution characteristic of the signal in the time-frequency field after wiping off the wide-band noise and fog noise, two methods, named the Throw Head and Tail Method and the Wipe Two Side Method, are supposed for the signal separation and combination. Both of these methods can increase the ability to recognize the conglutinating signal and to reinforce the signal.Fourthly, the devices of frequency hopping (FH) have been equipped in a large scale but it is also very difficult to recognize and reconnoiter the FH signal, in order to solve this problem, two methods are presented, named the Most Correlation Process Method and the Time Correlation Statistics Method. Good result can be achieved in theFH signal reconnaissance and recognition with the two methods.At last, in order to acquire the communication frequency the communication content of the other side in time, it is necessary to detect and recognize the ALE signals quickly. A method is presented in this paper, which is based on the result of wide-band signal separation and followed by the DDC processing and ALE detection and recognition. Compared with traditional method of narrow searching and detection, this method is faster in speed because it only detects and recognizes the frequency point that the signals exist.