Research On Active And Passive Composite Detection Target Signal Simulation And Recognition Technology In Complex Environmen

In view of the increasingly complex battlefield environment,active and passive composite detection can effectively identify armored targets in complex environments,which is a hot research topic at present.In this thesis,the following researches are carried out on target simulation and recognition technology for active and passive composite detection in complex environments:（1）Aiming at the influence of complex environments such as the atmosphere,rainfall,clouds and dust on the echo signal,this thesis establishes a millimeter wave attenuation model in a complex environment,and simulates the characteristic attenuation curve of the atmosphere,rainfall,clouds,and dust with the the path,antenna elevation angle,temperature,visibility and other conditions change.Combined with the change of the background brightness temperature in the complex environment,the change of the output waveform in the complex environment is simulated,and the attenuation value under different conditions is given.（2）Aiming at the low signal-to-noise ratio problem that may exist in the active and passive composite detection,the active channel in this thesis adopts the wavelet transform denoising algorithm and the spectrum refinement method based on the ap FFT time-shift phase difference method to improve the frequency measurement accuracy of the active channel.When the noise ratio is-15d B,the frequency measurement accuracy can reach10^-3 times the spectral line interval in the case of Gaussian white noise.The passive channel adopts a filtering and noise reduction algorithm based on moving average and Kalman filter.When the signal-to-noise ratio is as low as-30d B,the bell-shaped peak feature can be extracted well,which reduces the difficulty of extracting the feature value of the passive channel.（3）Aiming at the shortcomings of traditional constant false alarm rate（CFAR）algorithms that are easy to conceal small targets near the main target,an improved one-dimensional OS-CFAR and its two-dimensional form based on a cross window are designed,so that the threshold threshold can guarantee the false alarm rate.In this case,there is a greater probability of detecting adjacent targets.Aiming at the problem of insufficient fusion of traditional single decision-making layer information fusion,a two-layer information fusion method is designed,which adds feature layer fusion at the same time as the decision-making layer fusion,and combines the distance information of the active channel with the complex environment information to be input to the passive Channel,enhance the composite detection and recognition effect.（4）In order to verify the effectiveness of the active and passive composite detection signal processing algorithm in this article,the hardware design of the active and passive composite detection signal processing module was completed,and the signal processing code was written in verilog,and the target signal of the active and passive channel was tested by the tower test.And the recognition signal,by comparing with a single system,the recognition probability is increased by 13%～15%,which verifies the feasibility and effectiveness of the active and passive composite signal processing algorithm in this article.