A novel adaptive real-time image compression framework based on TMS320C6713 is presented in this paper. Via analyzing image texture, different compression ratio is applied for reducing the code stream. Owing to its lo...
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ISBN:
(纸本)9781849199940
A novel adaptive real-time image compression framework based on TMS320C6713 is presented in this paper. Via analyzing image texture, different compression ratio is applied for reducing the code stream. Owing to its low-cost, highspeed and low power performances, C6713 is selected as the main processor of framework. Firstly, the original image is transformed through lifting wavelet transform algorithm. Then, the resultant transformed data is encoded with zero tree wavelet, thereby completing the compression of 320x256 image with input bandwidth 2.34MB/s and output bandwidth 100kB/s. Moreover, the experimental results demonstrate that the adaptive image ratio can reach 25:1 with PSNR 30 and frame frequency can achieve 25fps with a high-speed processor.
A wideband PAR (Phased Array Radar) implementation framework based on wide band digital intermediate frequency is proposed for aperture full time problem. A method compensating the aperture full time by digital stretc...
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ISBN:
(纸本)9781849199940
A wideband PAR (Phased Array Radar) implementation framework based on wide band digital intermediate frequency is proposed for aperture full time problem. A method compensating the aperture full time by digital stretch processing for chirp signal is presented. A compensation approach for RF channels phase consistency using phase adjustment of digital oscillator is also given. Experiment results based on hardware system indicate that the method is effective and engineering realizable.
Space-surface bistatic synthetic aperture radar(SS-BiSAR) offers an additional observation angle for monostatic spaceborne SAR, making it a promising technology for high-accuracy deformation retrieval technology in lo...
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Space-surface bistatic synthetic aperture radar(SS-BiSAR) offers an additional observation angle for monostatic spaceborne SAR, making it a promising technology for high-accuracy deformation retrieval technology in local regions. Repeat-pass SS-BiSAR tomography can accurately estimate the surfaces of buildings and steep areas, effectively removing terrain phases during deformation retrieving. However, inaccuracies in the orbital ephemeris can lead to image geometry distortion, reducing image pair coherence,introducing interferometric phase errors, and consequently deteriorating tomographic precision. This paper precisely models the image geometry distortion and interferometric phase error caused by repeat-pass ephemeris error. We propose an ephemeris correction method based on the chirp-Z transform to address these issues. Furthermore, we introduce an accurate tomography model to improve 3D reconstruction *** first SS-BiSAR tomography experiment, conducted using the Chinese Lutan-1 satellite, demonstrates that the correlation coefficient is improved by 0.16 after ephemeris error correction. Moreover, the density and precision of the tomographic point cloud are improved by 13.7% and 12.1%, respectively.
The performance of the conventional Gram-Schmidt orthogonalization of covariance matrix (RGS) beamforming method will decrease significantly when non-ideal factors exists such as the appearances of fast moving interfe...
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ISBN:
(纸本)9781849199940
The performance of the conventional Gram-Schmidt orthogonalization of covariance matrix (RGS) beamforming method will decrease significantly when non-ideal factors exists such as the appearances of fast moving interferences, array platform movement. In order to improve the robustness of interference suppression, a derivative constrained Gram-Schmidt orthogonalization of covariance matrix (CRGS) beamforming method with widened nulls is proposed in this paper. In the proposed method, the number of interference P is initially estimated and the first subspace is reconstructed by Gram-Schmidt orthogonalization of the first P columns of sample covariance matrix. Afterwards, the derivative constrained vectors and the second subspace spanned of these vectors are constructed. At last the adaptive weight vector is obtained by orthogonally projecting the quiescent weight vector onto the interference subspace made up of the first subspace and the second subspace. Based on the numeral simulation results, it is verified that the proposed method can form widened nulls and effectively improve the robustness of interference suppression.
Phase autofocus is a key step of translational motion compensation (TMC) in inverse synthetic aperture radar (ISAR). In this paper, a modified phase autofocus algorithm is proposed for ISAR to improve the computationa...
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Slow-time MIMO radar is investigated to deal with some cost sensitive applications like UAVs detection to avoid the use of arbitrary waveform generators and digital receivers. But this method suffers from the deterior...
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Orthogonal projection (OP) adaptive beamforming is widely applied in practical scenarios because of strong robustness. However, the performance of traditional OP adaptive beamforming would degrade severely when OP ada...
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ISBN:
(纸本)9781849199940
Orthogonal projection (OP) adaptive beamforming is widely applied in practical scenarios because of strong robustness. However, the performance of traditional OP adaptive beamforming would degrade severely when OP adaptive beamforming is applied at subarray level, especially in asymmetrical subarray configuration. To overcome this problem, the improved orthogonal projection (IOP) adaptive beamforming based on normalization at subarray level is proposed. In the proposed method, the covariance matrix is firstly modified by normalizing the noise power at subarray level. Subsequently, the interference subspace is estimated by eigenvalue decomposition, and then the adaptive weight is calculated by using OP adaptive beamforming. Numeral simulation results show that the proposed method at subarray level outperforms the traditional OP adaptive beamforming and the output signal-to-interference-plus-noise ratio (SINR) is close to the optimum value. The proposed method can be significantly effective in practical applications.
Beam pattern synthesis is of great interest for colocated MIMO radar with larger aperture. Sever gating lobes and high sidelobe level would cause great performance loss when the transmitting array is sparse. In order ...
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This paper proposed a genetic algorithm based on division position coding to solve the optimization of subarray partition in monopulse application, which aims at finding the best compromise between sum and difference ...
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ISBN:
(纸本)9781849199940
This paper proposed a genetic algorithm based on division position coding to solve the optimization of subarray partition in monopulse application, which aims at finding the best compromise between sum and difference patterns. In the proposed method, the division position is encoded as a chromosome gene, then the initial population is randomly generated by a series of non-repeated integers, and the fitness calculation and genetic operation are subtly designed to improve the convergence and stability. Various numeral simulation results are presented to verify the effectiveness of the proposed method.
Conventional Space-time adaptive processing (STAP) requires large numbers of independent and identically distributed (i.i.d.) training samples to ensure the clutter suppression performance, which is hard to be achieve...
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ISBN:
(纸本)9781849199940
Conventional Space-time adaptive processing (STAP) requires large numbers of independent and identically distributed (i.i.d.) training samples to ensure the clutter suppression performance, which is hard to be achieved in nonhomogeneous environment. In order to obtain improved clutter suppression with small training support, an iterative sparse recovery STAP algorithm is proposed in this paper. In the proposed method, the clutter spectrum sparse recovery and the calibration of space-time overcomplete dictionary are implemented iteratively, modified focal underdetermined system solution (FOCUSS) with recursive calculation is used to alleviate the recovery error and reduce the computational cost, meanwhile the mismatch of space-time overcomplete dictionary is calibrated by minimized the cost function. Based on the simulated and the actual data, it is verified that the proposed method can not only converge with much smaller training samples compared with conventional STAP methods, but also provide improved performance compared with existing sparsity-based STAP methods.
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