dc.description.abstract |
The resolution requirements of remote sensing images become higher and the channel capacity from satellites to the ground stations is limited. In order to effectively reduce the image data of synthetic aperture radar and maintain good image resolution, a block adaptive quantizer (BAQ) is needed to compress the echo signals. In the BAQ, the input signals of the in-phase (I) and quadrature (Q) axes are divided into blocks. The statistics of each block such as the average energy is calculated to derive the parameters of Lloyd-Max quantizer including the thresholds and the representatives of each quantized region. The Lloyd-Max quantizer achieves the smallest mean square error (MSE) of the Gaussian distributed signals. The signal-to-noise ratio (SNR) based on the average energy of the input signals and the MSE of the quantized output is then evaluated. In our BAQ system, it can compress the ADC signals of 8,10,12,14 bits into 2, 3, 4, 6 or 8 bits outputs. The block size can be set as 128, 256 or 512 complex samples, and the whole possible variance range can be divided equally into either 128 or 256 segments depending on the user requirements.
When the BAQ output wordlength is large, the memory for storing the Lloyd-Max quantizer thresholds is huge. Thus, we propose to use variance scaling technique to normalize the input signal energy. In this case, only one set of thresholds is needed with an extra memory for storage of variance scaling values. Over 98% memory sizes can be saved. In order to get the output of non-uniform Lloyd-Max quantizer, a hybrid comparator architecture is designed. The number of adders and subtracters is also reduced. The hardware is first realized by the FPGA of Virtex-7 series. To achieve a higher operating frequency, parallel processing and pipeline techniques are used. The operating frequency can reach 500MHz. The design is also implemented in 40nm CMOS technology and the operating frequency achieves up to 800MHz with power consumption of 11.8mW. Thus, our design has good hardware efficiency and low power consumption. | en_US |