Jie Feng

Dr. Jie Feng


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 April 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Can LiuCan Liu
Can Liu
YLYunhua Luo
Yunhua Luo
Zhongjun YuZhongjun Yu
Zhongjun Yu
JFJie Feng
Jie Feng
This paper studies the inverse synthetic aperture radar imaging problem for a non-stationary moving target and proposes a non-search imaging method based on parameter estimation and sparse decomposition. The echoes received by radar can be thought of as consisting of chirp signals with varying chirp rates and center frequencies. Lv’s distribution (LVD) is introduced to accurately estimate these parameters. Considering their inherent sparsity, the signals are reconstructed via sparse representation using a redundant chirp dictionary. An efficient algorithm is developed to tackle the optimization problem for sparse decompositions. Then, by using the reconstructed data, adaptive joint time–frequency imaging techniques are employed to create high-quality images of the non-stationary moving target. Finally, the simulated experiments and measured data processing results confirm the proposed method’s validity.

27 January 2024 in Remote Sensing
Verified
Journal Article
Open access
PDF file
DCDongxu Chen
Dongxu Chen
TWTingcun Wei
Tingcun Wei
GLGaoang Li
Gaoang Li
JFJie Feng
Jie Feng
JZJialong Zeng
Jialong Zeng
Zhongjun YuZhongjun Yu
Zhongjun Yu
This paper investigates a real-time process generator of wideband signals, which calculates waveforms in a field-programmable gate array (FPGA) using the high-level synthesis (HLS) method. To obtain high-resolution and wide-swath images, the generator must produce multiple modes of large time-bandwidth product (TBP) linear frequency modulation (LFM) signals. However, the conventional storage method is unrealistic as it requires huge storage resources to save pre-computed waveforms. Therefore, this paper proposes a novel processing approach that calculates waveforms in real-time based simply on parameters such as the sampling frequency, bandwidth, and time width. Additionally, this paper implements predistortion through the polynomial curve to approximate phase errors of the system. The parallelizing process in the FPGA is necessary to satisfy the high-speed requirement of a digital-to-analog converter (DAC); however, repeatedly multiplexing real-time calculation consumes extensive logic and DSP resources, potentially exceeding FPGA limitations. To address this, this paper proposes a piecewise linear algorithm to conserve resources, which processes the polynomial only once, acquires the difference in two adjacent values through the register and pipeline, and then adds this increment to facilitate parallel computations. The performance of this proposed generator is validated through simulation and implemented in experiments with an X-band airborne SAR system.

25 March 2024 in Remote Sensing Letters
Verified
Journal Article
Closed access
WYWenbo Yu
Wenbo Yu
JLJiamu Li
Jiamu Li
ZWZijian Wang
Zijian Wang
ZYZhongjun Yu
Zhongjun Yu
YLYunhua Luo
Yunhua Luo
JFJie Feng
Jie Feng