The Parameter Estimation Of Wideb And LFM Signal Based On Compressive Sensing

Wideband LFM signal is a kind of large time bandwidth signal obtained by non-phase modulation, its low probability of intercept characteristic is an important reason for its wide application in radar countermeasure field, so it has important theoretical and practical value to realize the parameter estimation of wideband LFM signal. In this paper, we estimate the parameters of wideband LFM signal combined with Compressed Sensing under the condition of under sampling. The main work of this paper includes the following aspects:1. Proved wideband LFM signal has large time-bandwidth characteristics with the derivation of the formula, detailed introduces the compressed sensing theory, in order to estimate LFM signal parameter combined with compressed sensing theory better.2. Described the principle of fractional Fourier transform in detail, and estimate the parameter of the LFM signal using FRFT; The computation of parameter estimation of wideband LFM signal when estimated by FRFT directly is large. A method is proposed to estimate the parameter of wideband LFM signal combined FRFT with compressed sensing. It reduces the calculation and can accurately estimate the signal parameters, and the algorithm has strong anti-interference ability.3. Restricting by the current A/D sampling technology, parameter estimation of widebang LFM signal has signigicant research value. A novel parameter estimation method based on wavelet transform and compressed sensing(CS) theory is proposed. Since the wideband LFM signal has approximate tectangular spectrum, the wavelet transform is used for edge detection. The edges of widebang LFM signal spectrum are sparse relative to the wideband. Then we can obtain a sparse representation of inertest by the sparse transformation. The compressed sapling matching pursuit(Co Sa MP) algorithm is introduced to reconstruct the edge information of LFM signal spectrum from the sub-sampling LFM signals. The simulation results prove that the initial frequency and final frequency of wideband LFM signal can be estimated by the proposed method with high estimation precision. Aiming at the deficiency of Co Sa MP algorithm in pre-selection stage, cutting stage, sparsity, with fuzzy threshold method to optimize the algorithm, Co Sa MMP algorithm is proposed. Under the premise of not reducing the accuracy, it reduces the running time of the algorithm.4. The super-resolution estimation of frequency parameter can greatly increase the number of atoms in the over-complete dictionary and it will brings a huge amount of computation. To solve this problem, taking the feature of CS into account that the sampling and compression are completed at the same time, we structure a measurement matrix which can complete the compressive sampling and down-chirp simultaneously. Furthermore, we propose a down-chirp based method and improve it with fast computing strategy to solve the above problem. Simulation results have proved that the frequency parameter can be accurate estimated under a low SNR and sampling condition. The improved algorithm greatly reduces the scale of over-complete dictionary and the amount of computation, and the estimation time has been cut down significantly.