Simultaneous optimization of radar waveform and mismatched filter with range and delay-Doppler sidelobes suppression

Xu, Leilei; Zhou, Shenghua; Liu, Hongwei

doi:10.1016/j.dsp.2018.09.009

Cited by 12 publications

(2 citation statements)

References 26 publications

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“…In their work, the pulse number and code length of CCS are no longer restricted, but there still is room to improve the Doppler tolerance. Recently, the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm was used to optimize the AF of CCS [35][36][37]; however, the efficiency and the obtained optimal result still can be further improved.…”

Section: Introductionmentioning

confidence: 99%

Joint Design of Complementary Sequence and Receiving Filter with High Doppler Tolerance for Simultaneously Polarimetric Radar

Chen,

Zhang,

et al. 2023

Remote Sensing

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Simultaneously polarimetric radar (SPR) realizes the rapid measurement of a target’s polarimetric scattering matrix by transmitting orthogonal radar waveforms of good ambiguity function (AF) properties and receiving their echoes via two orthogonal polarimetric channels at the same time, e.g., horizontal (H) and vertical (V) channels (antennas) sharing the same phase center. The orthogonality of the transmitted waveforms can be realized using low-correlated phase-coded sequences in the H and V channels. However, the Doppler tolerances of the waveforms composed by such coded sequences are usually quite low, and it is hard to meet the requirement of accurate measurement regarding moving targets. In this paper, a joint design approach for unimodular orthogonal complementary sequences along with the optimal receiving filter is proposed based on the majorization–minimization (MM) method via alternate iteration for obtaining simultaneously polarimetric waveforms (SPWs) of good orthogonality and of the desired AF. During design, the objective function used for minimizing the sum of the complementary integration sidelobe level (CISL) and the complementary integration isolation level (CIIL) is constructed under the mismatch constraint of signal-to-noise ratio (SNR) loss. Different SPW examples are given to show the superior performance of our design in comparison with other designs. Finally, practical experiments implemented with different SPWs are conducted to show our advantages more realistically.

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Section: Introductionmentioning

confidence: 99%

Joint Design of Complementary Sequence and Receiving Filter with High Doppler Tolerance for Simultaneously Polarimetric Radar

Chen,

Zhang,

et al. 2023

Remote Sensing

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show abstract

“…In [22], the authors took the maximum SNR loss as a constraint to optimize the PSLR and the PCCL, while in [23], the authors took the PSLR and the PCCL as constraints to optimize the interference and jamming power. In recent years, a simultaneous optimization of the waveform and mismatched filter was proposed in [24] to suppress the sidelobe. In [25], the authors used the convex optimization method to design the ultra-low sidelobe for the LFM signal.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Weighting Window Functions for SAR Imaging via QCQP Approach

Liu

Wang

Song

2020

Sensors

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Weighting window functions are commonly used in Synthetic Aperture Radar (SAR) imaging to suppress the high Peak SideLobe Ratio (PSLR) at the price of probable Signal-to-Noise Ratio (SNR) loss and mainlobe widening. In this paper, based on the method of designing a mismatched filter, we have proposed a Quadratically Constrained Quadratic Program (QCQP) approach, which is a convex that can be solved efficiently, to optimize the weighting window function with both amplitude and phase, expecting to offer better imaging performance, especially on PSLR, SNR loss, and mainlobe width. According to this approach and its modified form, we are able to design window functions to optimize the PSLR or the SNR loss under different kinds of flexible and practical constraints. Compared to the ordinary real-valued and symmetric window functions, like the Taylor window, the designed window functions are complex-valued and can be asymmetric. By using Synthetic Aperture Radar (SAR) point target imaging simulation, we show that the optimized weighting window function can clearly show the weak target hidden in the sidelobes of the strong target.

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Ambiguity Function Analysis of Polyphase Codes in Pulse Compression Radars

Thakur

Saini

2020

Computing Algorithms With Applications in Engineering

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Simultaneous optimization of radar waveform and mismatched filter with range and delay-Doppler sidelobes suppression

Cited by 12 publications

References 26 publications

Joint Design of Complementary Sequence and Receiving Filter with High Doppler Tolerance for Simultaneously Polarimetric Radar

Joint Design of Complementary Sequence and Receiving Filter with High Doppler Tolerance for Simultaneously Polarimetric Radar

Optimization of Weighting Window Functions for SAR Imaging via QCQP Approach

Ambiguity Function Analysis of Polyphase Codes in Pulse Compression Radars

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