Optimization in Detection of Moving Targets With noise-like waveform and based on compressed sensing

using Smart antennas were used in special applications such as military radars, but with the emergence of a lack of capacity in the provision of telecommunication services, should be able to estimate the reception angle of each user, as well as the ability to track the reception of the signal. In this case, the smart antenna can set its own beam for each user so that the signal-to-noise ratio and the interference of each user are maximized and thus increase the capacity of the system. Contract procedures based on the beam shaping techniques of beam It is classic and requires a lot of elements to achieve high precision. The maximum likelihood methods of fine-tuning are optimal techniques that work well even under low SNR conditions, but are often computational complicated. But in sub-space-based methods, high precision techniques are required that specific structure of the input data matrix. These methods can motion be MUSIC, ESPRIT, and Min Norm-complete correlations, or coherence. Leads to a specific error in these methods. After solving a integration error, another problem that occurs in high-resolution incoming angle estimation methods is the variation of noise power between the sensing and the other sensing. The presence of variable noise power in spatial smoothing methods with a high signal-to-noise ratio is somewhat solvable, but with increasing power and also the lack of access to the signal-to-noise ratio, these methods also fail. In addition, under these conditions, methods based on sub-sub arrays that are the only solution have very low estimate. Therefore, in this paper, the SSFx algorithm will be used to calculate the angles of entry to the correlated form. The proposed model addresses the problem of coherence and asymmetry of sub arrays. The method discussed in this paper no longer requires the direct calculation of the inverse matrix and is based on the repetition of this procedure and acts in the collision with the coherent and non-coherent signal. In the end, the results indicate that The proposed algorithm has a higher resolution rate than unconnected algorithms and is resistant to low SNRs. And because of the above data, the compressive sensing based method for noise isolation is used, which, in addition to reducing the number of samples required from the radar receiver output signal, increases the system s radar performance.

Keywords:

Signal-to-Noise Ratio (SNR) , Direction Of Arrival Algorithm (DOA) , MUSIC Algorithm , Signal Subspace Focusing (SSF)