Detection And Modulation Parameters Estimation Of Multi-Signals Under Compressed Sampling

In recent years, wireless communication technology has been rapidly developed toaccommodate to the increasingly complicated electromagnetic environment, consequently tochallenge the communication reconnaissance field. Especially along with application andpopularization of cognitive radio, in electronic reconnaissance systems, receiving and real-timeparallel computing for broadband multi-signals are essential. When wide multiband signals aredetected by the traditional method which is based on the present Nyquist sampling theorem,thediffieulty of hardware will be greatly increased. The “Compressed Sensing” analog acquisitionsystem can break through the restrictions of huge data and hardware, so it will be the trend inwideband signal processing.In many wideband non-cooperative recieving situations such as in signal interception,spectrum sensing and communication reconnaissance,the observed signals are generally analiasing of several narrowband modulated signals which distributed over the band of receiver. Ithas been defined as wideband sparse signals due to the sparsity of spectrum. Just oncommunication reconnaissance condition, this thesis realized the detection and modulationanalysis of wideband sparse signals by processing compressed measurements directly. The keywork and innovations are summarized as follows:1、Combining with the characteristics of wideband sparse signals and physical meaning ofCompressed Sensing,the mathematical model of compressed sensing multi-signals is established.Then the theoretical basis of inducting cyclostationary tools is indicated and the processing flowof compressed sensing multi-singals blind detection and modulation analysis are given briefly.2、For the existence detection of multi-signals which were received by single channel, analgorithm based on numerical characteristics of compressed measurements is proposed.According to the different characteristics of the expectation of compressed measurements underdifferent hypothesis, detection is accomplished by using the deviation of the actual samplingvalues from the expectations under corresponding hypothesis as criterion.3、Proposed a source number esimation algorithm via the symmetry of cyclic spectrum. Thecalculating equation of cyclic spectrum is derived directly via compressed measurements ratherthan reconstructing the original waveform. An improvement on Orthogonal Matching Pursuitalgorithm is given in the process of calculating. The terminated condition is according to thechange rate of iterative error. Then the source number could be estimated accurately in a shorttime and it is more flexible in practical implementation.4、The matrix relationship between compressed measurements and high-order cycliccumulants has been established. With the sparsity and differentiation in cyclostationary, cyclic cumulants are estimated as the final destination. Modulation parameters of each componentcould be estimated by matching carrier frequency or symbol rate with the corresponding cyclicfrequency.5、The modulation recognition for multi-signals is presented which is based on thecyclostationary characteristics.On the premise of the known modulation parameters, a classifieris designed to realize the modulation recognition for multi-signals,which is based on the value ofdissimilar order cyclic cumulants in corresponding cyclic frequency location.