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The paper presents different processing schemes that have been investigated in order to evaluate the direction of arrival (DOA) with a multiple-input multiple-output (MIMO) radar. Conventional digital beam forming (DBF) and super resolution algorithm (MUSIC) have been applied. The results provided by them have been compared with a compressive sensing (CS) processing of the virtual elements of the MIMO array. The possible reduction of the number of physical elements in the array, due to the application of CS techniques, has been also analyzed. Experimental validation has been carried out on a test board radar developed at TNO in the Netherlands.

In this paper, four different array radar concepts are compared: pencil beam, floodlight, monostatic MIMO, and multistatic MIMO. The array radar concepts show an increase in complexity accompanied by an increase in diversity. The comparison between the radar concepts is made by investigating the detection performance for a surveillance task in various environments, including an urban environment.

The authors present a 2D-MUSIC processing for the simultaneousestimation of angular and range target positions. A2D spatial smoothing technique is also introduced in orderto cope with the coherent behavior of the received echoes, which may result in a rank deficiency of the signals covariancematrix. The algorithm is analyzed with respect to its application to coherent MIMO arrays. The extended baseline which is synthesised can indeed be used to further increasethe performances of the system. Results of the algorithmare shown for both simulated and experimental data scenarios. In the latter case, the data are collected by an FMCW radar with MIMO functionality that has been designedand realized in cooperation with TNO, the Netherlands.

Multiple-input-multiple-output (MIMO) processing is a consolidated technique in communication systems thanks to the benefits that it offers in multipath fading environments. In recent years, studies have shown how the performances of conventional phased-array radar can be improved by using the same approach. This letter illustrates how the digital beamforming (DBF) theory can be extended to include MIMO arrays. In particular, the general description of a MIMO pattern is retrieved; accordingly, two different designs are described, which are aimed at obtaining optimal angular resolution and at controlling the sidelobes of the synthetic array pattern. An experimental result of a pattern synthesis is presented in the last section of the letter.

In this paper we present a technique to estimate the calibration coefficients of a coherent Multiple-Input Multiple-Output (MIMO) array radar built on a printed circuit board (PCB). Due to the integrated structure and the MIMO nature of the system, a direct measurement of each antenna element behavior cannot be performed. The proposed method is based on the evaluation of the calibration parameters from the signal reflected by dominant targets, located at different range bins, and it does not require the a priori knowledge of their angular positions. Experimental validation of the presented technique has been done and the related results are illustrated. © 2012 IEEE.

In this paper, a new signal processing technique for Multiple-Input Multiple-Output (MIMO) image processing of a Linear Frequency-Modulated Continuous Wave (LFMCW) automotive radar was developed. The image is the range-speed-direction data cube. The technique comprises two improvements to the standard MIMO image processing: 1) A fast unambiguous Doppler target detection. 2) An improved direction finding with estimated virtual antenna elements besides the synthesized virtual antenna elements. High speed automotive targets go through several range cells in the observation period making it difficult to obtain coherent accumulated power. Another problem with high speed targets in combination with a low Sweep Repetition Frequency (SRF) is ambiguous Doppler speed measurement. In order to remove range migration and obtain coherent accumulated power the keystone transform is applied. The direction finding resolution depends on the number of transmitter- and the receiver elements of the MIMO configuration. A combination of the transmitter and receiver elements give synthesized virtual elements with corresponding antenna width. In order to improve the direction finding, the antenna width with extrapolated virtual antenna elements was extended. The Band Width Extrapolation (BWE) method is applied for estimating these extrapolated virtual antenna elements. The proposed method is verified by simulation and real radar measurements. © 2013 European Microwave Association.

In this paper, a new signal processing technique for Multiple-Input Multiple-Output (MIMO) image processing of a Linear Frequency-Modulated Continuous Wave (LFMCW) automotive radar was developed. The image is the range-speed-direction data cube. The technique comprises two improvements to the standard MIMO image processing: 1) A fast unambiguous Doppler target detection. 2) An improved direction finding with estimated virtual antenna elements besides the synthesized virtual antenna elements. High speed automotive targets go through several range cells in the observation period making it difficult to obtain coherent accumulated power. Another problem with high speed targets in combination with a low Sweep Repetition Frequency (SRF) is ambiguous Doppler speed measurement. In order to remove range migration and obtain coherent accumulated power the keystone transform is applied. The direction finding resolution depends on the number of transmitter-and the receiver elements of the MIMO configuration. A combination of the transmitter and receiver elements give synthesized virtual elements with corresponding antenna width. In order to improve the direction finding, the antenna width with extrapolated virtual antenna elements was extended. The Band Width Extrapolation (BWE) method is applied for estimating these extrapolated virtual antenna elements. The proposed method is verified by simulation and real radar measurements. © 2013 EMA.

A coherent two-dimensional (2D) multiple signal classification (MUSIC) processing for the simultaneous estimation of angular and range target positions has been presented. A 2D spatial smoothing technique is also introduced to cope with the coherent behaviour of the received echoes, which may result in a rank deficiency of the signals covariance matrix. The algorithm is analysed with respect to its application to coherent multiple-input multiple-output (MIMO) arrays. The extended baseline which is synthesised can indeed be used to further improve the performance of the system. The results of the algorithm are shown for both simulated and experimental data scenarios. In the latter case, the data are collected by a frequency-modulated continuous wave radar with MIMO functionality that has been designed and realised in cooperation with TNO, the Netherlands. © The Institution of Engineering and Technology 2014.

In this paper the authors analyze the use of Time Division Multiple Access (TDMA) applied to coherent Multiple-Input Multiple-Output (MIMO) radar systems. One of the main limitations in exploiting the orthogonal condition in the time domain for MIMO radars is the reduction of the unambiguous Doppler interval. With respect to frequency modulated continuous waveform (FMCW) systems, the authors present a possible solution which is based on the introduction of a random selection of the active transmitter. The analytical representation of the signal model is described and the simulated results of the proposed approach are shown. © 2012 IEEE.

In this article a novel waveform, Random SlowTime Code Division Multiple Access (ST-CDMA) for MIMO radar is presented and investigated. ST-CDMA means that the waveforms of the different transmitters are orthogonal per burst, while conventional CDMA implies orthogonal waveforms of the different transmitters per pulse. In particular, the Doppler ambiguity performance of the proposed Random ST-CDMA waveform is compared to that of the well-known Doppler Division Multiple Access (DDMA) waveform, which is a specific type of STCDMA. Both in combination with conventional processing (based on matched filters) and with Sparse Signal Processing (SSP) the DDMA waveform yields a reduction in unambiguous Doppler range as compared to other MIMO waveforms, such as CDMA. Instead, the Random ST-CDMA waveform together with SSP yields no reduction in unambiguous Doppler Range and improved side lobe suppression.