Abstract
This study presents MIMO radar in food density measurement signal separation method-INN-LCMV adaptive pulse compression method based on Linear Constrained Minimum Variance (LCMV) criterion and infinite norm normalization method. In the presented method, unrequited transmit signal and non-Gaussian noise are regarded as interference, the received signals are processed in the infinity norm normalization method, the weight coefficients of the filter based on the linear constrained minimum variance are derived. The simulation results show that, this method is suitable for the non-Gaussian noise, the influence of noise on signal separation performance is relatively small, the proposed method is very efficient for MIMO radar in food density measurement signal separation in non-Gaussian noise.
Highlights
Multi-Input Multi-Output radar (MIMO) is a relatively new technology in the non-destructive testing world
MIMO radar in food density measurement is a new radar in food density measurement system, it is a hot field of radar in food density measurement theory and experimental research in recent years (Fishler et al, 2004a), MIMO radar in food density measurement emits a set of orthogonal waveform, forming a low gain wide beam, the receiver uses a set of matched filters to separate the orthogonal waveform, its target detection performance and low probability of intercept are superior to the conventional radar in food density measurement (Fishler et al, 2004b; Li et al, 20l0)
Simulation and analysis: In order to verify MIMO radar in food density measurement signal separation performance of the proposed method, respectively simulated using the proposed method, Linear Constrained Minimum Variance (LCMV) adaptive pulse compression method, LCMV adaptive pulse compression based on fractional lower order statistics method and the traditional matched filter method
Summary
Multi-Input Multi-Output radar (MIMO) is a relatively new technology in the non-destructive testing world. MIMO radar in food density measurement is a new radar in food density measurement system, it is a hot field of radar in food density measurement theory and experimental research in recent years (Fishler et al, 2004a), MIMO radar in food density measurement emits a set of orthogonal waveform, forming a low gain wide beam, the receiver uses a set of matched filters to separate the orthogonal waveform, its target detection performance and low probability of intercept are superior to the conventional radar in food density measurement (Fishler et al, 2004b; Li et al, 20l0). MIMO radar in food density measurement requires transmitted waveform is orthogonal waveform, but completely orthogonal waveform does not exist. We can use the orthogonal MIMO radar in food density measurement wave form design and signal separation to solve. A set of ideal orthogonal waveform must meet the cross-correlation function of two arbitrary waveform is zero, the autocorrelation function has a very low peak sidelobe level, in practice, completely orthogonal transmit signals is not exist in a variety of environments. In order to improve the effect of signal separation, to design a pulse compressed filter that can be effectively separated signal is necessary
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