Ieee transactions® on aerospace and electronic systems

Radar is an acronym for "radio detection and ranging." However, the functions of today's radar systems, both in civilian and military applications, go beyond simple target detection and localization; they extend to tracking, imaging, classification, and more and involve different types of radar systems, such as through-the-wall [1], ground-penetration [2], automotive [3], and weather [4]. Although radar technology has been well established for decades, a new line of compressed radars has recently emerged. These aim at reducing the complexity of classic radar systems by exploiting inherent prior information on the structure of the received signal from the targets. The goal of this article is to review these novel sub-Nyquist radars and their potential applications.

Sub-Nyquist Radar Systems: Temporal, Spectral, and Spatial Compression

ISCASはIEEE Circuits and Systems Societyが主催する 回路とシステムに関する国際会議で,今年は5月20日から5 月23日にかけて,韓国のソウルで開催された. ISCASは,「回路とシステム」に関する国際会議としては最 大規模かつ最も権威のある学会である.近年は,専門性を重視 した国際会議が増える中,ISCASは回路とシステムに関する 総合大会的な会議の立ち位置を維持し続けている.今年の会議 テーマは,“Convergence of BINET (Bio, Info, Nano, and Enviro Technology)”ということで,近年注目されている生物 学やナノ及び環境テクノロジーに関する論文をはじめ,これま で同様にアナログ信号処理,ディジタル信号処理,通信用回路, 非線形回路,パワーエレクトロニクス,VLSIシステムなど多 岐にわたる分野から論文投稿が行われた.テクニカルプログラ ムとしては,14のトラックからプログラムが構成され,102 のレクチャーセッション,52のポスターセッション,及び四 つのライブデモセッションが組まれた.レギュラートラックに 限れば,投稿総数1,651件に対して741件の論文が採録され, 採択率は44.9 %であった.なお,スペシャルセッション,デ モセッションを含めると1,760件の投稿数で822件が採録さ れ,採択率は46.7 %であった.ISCASが目標としている採 択率50 %以下を今年も維持する結果となった.また,3人の 世界的に著名な研究者による基調講演が会議のテクニカルプロ グラムの質を更に向上させることになった. ソーシャルイベントもかなり充実していた.初日のウェルカ ムレセプションでは,氷でできたISCAS2012の彫刻が我々 参加者を迎えてくれ,世界各国の料理が振る舞われた. また,会場ステージでは,CASSメンバーによって結成され たCASSバンドの演奏があり,大いに盛り上がりを見せた.三 日目のバンケットでは,韓国の伝統芸能と,K-POPスターの 4MINUTEのステージがあり,韓国のエンターテイメントのす ごさを実感することができた.最終日のフェアウェルパーティ は,韓国国立博物館で開催され,まず博物館で韓国の歴史や 文化を学んだあと,参加者との最後の別れを交わすパーティが 始まった.ここでは,巨大ビビンバやマッコリが振る舞われ, 韓国の食文化を存分に味わうことができた.このようにして, ISCAS 2012はテクニカルプログラム及びソーシャルプログ ラム共に大成功して幕を閉じた. 来年のISCAS 2013は5月19日~23日に中国の北京で 開催されます.私はもちろん参加します!!皆さん,来年中国 でお会いしましょう!!

国際会議開催報告:IEEE International Symposium on Circuits and Systems

We investigate the one-bit MIMO (1b-MIMO) radar that performs one-bit sampling with a time-varying threshold in the temporal domain and employs compressive sensing in the spatial and Doppler domains. The goals are to significantly reduce the hardware cost, energy consumption, and amount of stored data. The joint angle and Doppler frequency estimations from noisy one-bit data are studied. By showing that the effect of noise on one-bit sampling is equivalent to that of sparse impulsive perturbations, we formulate the one-bit $\ell _1$ -regularized atomic-norm minimization (1b-ANM-L1) problem to achieve gridless parameter estimation with high accuracy. We also develop an iterative method for solving the 1b-ANM-L1 problem via the alternating direction method of multipliers. The Cram $\acute{\text{e}}$ r-Rao bound (CRB) of the 1b-MIMO radar is analyzed, and the analytical performance of one-bit sampling with two different threshold strategies is discussed. Numerical experiments are presented to show that the 1b-MIMO radar can achieve high-resolution parameter estimation with a largely reduced amount of data.

Gridless Parameter Estimation for One-Bit MIMO Radar With Time-Varying Thresholds

We consider a multiple-input multiple-output (MIMO) radar that works through one-bit sampling of received radar echoes. The application of one-bit sampling significantly reduces the hardware cost, energy consumption, and systematic complexity, but it also poses serious challenges to extracting highly accurate target information from one-bit quantized data. In this article, we propose a maximum likelihood (ML)-based method that first iteratively maximizes the likelihood function to recover a virtual array data matrix and then jointly estimates the angle and Doppler parameters from the recovered matrix. Because the ML problem is convex, we can successfully apply a computationally efficient gradient descent algorithm to solve it. Based on our analysis of the Cram $\acute{\text{e}}$ r–Rao bound of the ML-based method, a pre-estimation-assisted threshold (PET) strategy is developed to improve the estimation performance. Numerical experiments demonstrate that the proposed ML-based method, combined with the PET strategy, can provide highly accurate parameter estimation performance, close to that of the classic MIMO radar.

Joint Angle and Doppler Frequency Estimation for MIMO Radar with One-Bit Sampling: A Maximum Likelihood-Based Method

Quadrature compressive sampling (QuadCS) is a recently introduced sub-Nyquist sampling scheme for effective acquisition of inphase and quadrature (I/Q) components of sparse radio frequency signals. In applications to pulse-Doppler radars, the QuadCS outputs can be arranged into a two-dimensional data format, in terms of slow time and virtual fast time, similar to that by Nyquist sampling. This paper develops a compressive sampling pulse-Doppler (CoSaPD) processing scheme which performs Doppler estimation/detection and range estimation from the sub-Nyquist data without recovering the Nyquist samples. The Doppler estimation is realized through a spectrum analyzer as in classical processing, whereas the detection is performed using the Doppler bin data. The range estimation is performed using sparse recovery algorithms only for the detected targets to reduce the computational load. A low detection threshold is used to improve the detection probability and the introduced false targets are then removed in the range estimation stage by exploiting the inherent target detection capability of the recovery algorithms. Simulation results verify the effectiveness of the proposed CoSaPD scheme, which requires only one-eighth of the Nyquist rate to achieve similar performance to the classical processing with Nyquist samples, provided that the input signal-to-noise ratio (SNR) is above −25 dB.

Pulse-doppler signal processing with quadrature compressive sampling

Quadrature compressive sampling (QuadCS) is a newly introduced sub-Nyquist sampling for acquiring inphase and quadrature (I/Q) components of radio-frequency signals. For applications to pulse-Doppler radars, the QuadCS outputs can be arranged in 2-dimensional data similar to that by Nyquist sampling. This paper develops a compressive sampling pulse-Doppler (CoSaPD) processing scheme from the sub-Nyquist samples. The CoSaPD scheme follows Doppler estimation/detection and range estimation and is conducted on the sub-Nyquist samples without recovering the Nyquist samples. The Doppler estimation is realized through spectrum analyzer as in classic processing. The detection is done on the Doppler bin data. The range estimation is performed through sparse recovery algorithms on the detected targets and thus the computational load is reduced. The detection threshold can be set at a low value for improving detection probability and then the introduced false targets are removed in the range estimation stage through inherent detection characteristic in the recovery algorithms. Simulation results confirm our findings. The CoSaPD scheme with the data at one eighth the Nyquist rate and for SNR above -25dB can achieve performance of the classic processing with Nyquist samples.

Pulse-Doppler Signal Processing with Quadrature Compressive Sampling

A blind stopping condition for orthogonal matching pursuit with applications to compressive sensing radar

Block sparse representation and suppression of narrow-band interference signals for quadrature compressive sampling radar

Quadrature compressive sampling (QuadCS) is a newly introduced sub-Nyquist sampling for acquiring inphase and quadrature components of radio-frequency signals This paper develops a target detection scheme of pulsed-type radars in the presence of digital radio frequency memory (DRFM) repeat jammers with the radar echoes sampled by the QuadCS system For diversifying pulses, the proposed scheme first separates the target echoes from the DRFM repeat jammers using CS recovery algorithms, and then removes the jammers to perform the target detection Because of the separation processing, the jammer leakage through range sidelobe variation of the classical match-filter processing will not appear Simulation results confirm our findings The proposed scheme with the data at one eighth the Nyquist rate outperforms the classic processing with Nyquist samples in the presence of DRFM repeat jammers

Chao Liu

Papers

Pulse-doppler signal processing with quadrature compressive sampling

Pulse-Doppler Signal Processing with Quadrature Compressive Sampling

A blind stopping condition for orthogonal matching pursuit with applications to compressive sensing radar

Block sparse representation and suppression of narrow-band interference signals for quadrature compressive sampling radar

Anti-jamming target detection of pulsed-type radars in QuadCS domain