Dazhi Zeng

Design of a correlated Lognormal distributed sequence generator based on Virtex-IV series FPGA

Proposed is a hardware correlated Lognormal distributed sequence generator based on the Virtex-IV XC4VFX100-10 FPGA. The random number is generated by the improved Tausworthe architecture and the non-correlated Gaussian random sequence is generated by Box-Muller algorithm. The correlated Lognormal distributed sequence is generated by zero memory non-linearity transformation with the proposed digital architecture. The complex cepstrum is used in the proposed frequency filter to generate the correlated coefficient. The logarithmic and exponential functions are calculated with CORDIC IPCore. The implementation on FPGA occupies 4210 slices, 4 block RAM and 2 DSP48s. The numeral experiment show the feasibility and accuracy of the proposed method. This proposed Lognormal distributed sequence generator can be used as a key component in a hardware radar echo and clutter simulator.

Application of digital parallel technology in the GNSS signal generator

This paper presents the architecture of the RF GNSS signal generator, which can output the L-band GNSS signal directly without the analog up-converter, and a prototype base on the architecture. This generator is a typical application of the digital parallel technology, since the key points of the design are all concerned with it. The generator can meet the demands of the various GNSS frequencies and overcomes the problems the analog up-converter brings, like temperature drift, etc. Meanwhile, the system integration is improved.

Parameter estimation of moving target for stepped-frequency radar under temporal-correlated clutter

Proposed is a maximum likelihood (ML) estimation method to estimate the parameter of the moving target for high range resolution stepped-frequency radar in strong clutter background. In this study the temporal correlated clutter is used. By transmitting frequency-hopping waveform and using the spectrum density of the clutter, the method may accurately estimate the moving target parameter in strong clutter. Numerical experiments illustrate the effectiveness of the proposed method.

Parameter estimation for stepped-frequency radar under temporal-spatial correlated clutter

Proposed is a maximum likelihood (ML) estimation and minimum target error function (TEF) method to estimate the parameters of the moving target for high range resolution stepped-frequency radar in temporal-spatial correlated clutter background. The compound-Gaussian model is used for the temporal-spatial correlated clutter. Both of the velocity and range of the moving target can be accurately estimated for stepped-frequency radar. Numerical experiments illustrate the effectiveness of the proposed method.