Design of Radar Receive Filters Optimized According to $L_{p}$-Norm Based Criteria

Maio, Antonio De; Huang, Yongwei; Piezzo, Marco; Zhang, Shuzhong; Farina, A.

doi:10.1109/tsp.2011.2153199

Cited by 48 publications

(26 citation statements)

References 11 publications

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“…Based on the above considerations, it is not surprising that the design of optimized Doppler processors has been a hot research activity within the radar community since 60's [4], [5], [6]. In fact, many studies have been directed toward the synthesis of advanced and highly performing nonadaptive/adaptive filters fulfilling the more and more stressing radar performance requirements [7], [8], [9], [10], [11], [12], [13].…”

Section: Motivation Notation and Problem Formulationmentioning

confidence: 99%

Robust Design of Radar Doppler Filters

Aubry

Maio

Huang

et al. 2016

IEEE Trans. Signal Process.

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This paper considers the design of robust filters for radar pulse-Doppler processing when the interference is a wide sense stationary random process. The figure of merit which is optimized is the Signal-to-Interference-plus-Noise Ratio (SINR) at the filter output under a multitude of constraints accounting for Doppler filter sidelobes as well as uncertainties both in the received useful signal component and interference covariance matrix. The design is analytically formulated as a constrained optimization problem whose feasibility is thoroughly studied. Besides, a polynomial-time solution technique to get the optimal filter is proposed exploiting the representation of non-negative trigonometric polynomials via linear matrix inequalities, the spectral factorization theorem, and the duality theory. Last but not least, a detailed analysis of the optimum filter performance is provided showing the trade-offs involved in the design and the gain achievable over some already known counterparts.

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Section: Motivation Notation and Problem Formulationmentioning

confidence: 99%

Robust Design of Radar Doppler Filters

Aubry

Maio

Huang

et al. 2016

IEEE Trans. Signal Process.

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“…The PSL minimization mostly corresponds to a minimization of the mainlobe width, which is determined by the level of higher sidelobes directly adjacent to the main peak. A unifying approach implementing both objectives can be obtained by formulating a sidelobe level cost function based on the L p -norm [10], [12]. Let…”

Section: Filter Designmentioning

confidence: 99%

“…A mismatched filter (MMF) [7], [8] can alternatively be used, which compromises SNR to improve on the described shortcomings of the matched filter. In the context of radar signal processing this filter is called 'instrumental variable filter' (IV) [9], [10]. For GSM-based PBR, MMF methods have been studied in order to reduce the mentioned sidelobes [11].…”

Section: Introductionmentioning

confidence: 99%

“…These methods were SNR-sensitive and require a high target SNR which is not always given. Other approaches to design an IV filter for sidelobe minimization can be found in [10], [12], [13], but they do not allow explicit regulation of the noise sensitivity of the filter. In this paper, the design and implementation of an instrumental variable filter with controlled SNR-loss in PBR are discussed.…”

Section: Introductionmentioning

confidence: 99%

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Mismatch loss constrained instrumental variable filtering for GSM passive bistatic radar

Bahlke

Zemmari

Nickel

et al. 2014

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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In this paper we address the design and evaluation of a mismatched filter for application in GSM passive bistatic radar (PBR). We discuss various exisiting approaches for the filter design, which originate from active radar systems and have to be adapted for PBR. Our proposed method minimizes the Lp-norm of the sidelobe level energies under an upper-bound constraint on the SNR loss relative to the matched filter. We show the suitibility of this approach for GSM based PBR and give a performance evaluation. Based on simulated and measured data, we show that the proposed filter can improve range resultion and target detection of the PBR system

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“…Optimized mismatched filtering, where the filter is typically obtained via Least Squares (LS) [6] or possibly via L p norm minimization [7,8], can achieve sidelobe levels much lower than the matched filter (depending on the waveform) while incurring a rather small mismatch loss. Being nonadaptive, the LS MMF seeks to minimize the sidelobe response at all delay shifts included in the signal model as it is unknown a priori which, if any, relative delays require lower sidelobes (since the range profile is unknown).…”

Section: Introductionmentioning

confidence: 99%

Practical aspects of optimal mismatch filtering and adaptive pulse compression for FM waveforms

Henke

McCormick

Blunt

et al. 2015

2015 IEEE Radar Conference (RadarCon)

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The sensitivity impact of range straddling in the form of mismatch loss is well known. What is less appreciated, however, is the effect upon dynamic range, particularly for receive filtering that seeks to minimize range sidelobes. For FMbased waveforms, which are readily implementable in a highpower radar system, it is shown that least-squares (LS) mismatched filtering (MMF) realizes a penalty in sidelobe suppression when range straddling occurs. This degradation can be partially compensated through modification of the LS MMF implementation. Alternatively, adaptive pulse compression (APC), appropriately modified for application to FM waveforms, demonstrates robustness to both straddling and eclipsing effects. Simulated and experimentally measured results are provided to demonstrate the efficacy of these filtering approaches.

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Design of Radar Receive Filters Optimized According to $L_{p}$-Norm Based Criteria

Cited by 48 publications

References 11 publications

Robust Design of Radar Doppler Filters

Robust Design of Radar Doppler Filters

Mismatch loss constrained instrumental variable filtering for GSM passive bistatic radar

Practical aspects of optimal mismatch filtering and adaptive pulse compression for FM waveforms

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