Interleaved OFDM Signals for MIMO Radar

This article presents two-dimensional (2-D) scattering centres' parameter estimation based on linear uniform multi-input multi-output (MIMO) radars. Unlike single-input single-output (SISO) radars, MIMO radars transmit multiple detection signals at the same time. We assume that each antenna of a MIMO radar transmits signals with a set of different spread spectrum codes so as to distinguish the echoes from all antennas. Then, with spread spectrum and de-spread spectrum techniques, each antenna of a MIMO radar could distinguish its own stepped-up frequency echoes transmitted by itself. In this article, we take m sequences as spread spectrum codes and assume that the ratio between the MIMO radars array aperture and the target distance is much less than 1, then we use 2-D fast Fourier transform (FFT) and matrix extended matrix pencil (MEMP) methods to extract 2-D scattering centres' parameters after MIMO radar have received de-spread echoes. Simulations illustrate that both SISO radars and linear uniform MIMO radars using the spread spectrum technique can get similar estimation results, and the MEMP method can afford super-resolution estimation results, whereas the 2-D FFT method is more useful when the number of MIMO radar array elements are no more than the number of scattering centres.

Space time coding plays quite an important role in the design of multi-input multi-output (MIMO) radar. It has been shown that the correlation characteristics of waveform set have a great impact on the performance of target detection and localisation for MIMO radar. In this study, the target detection and localisation performance of co-located MIMO radar is analysed theoretically and experimentally, when correlated (not ideally orthogonal or fully coherent) waveforms are transmitted. The relationship between transmit–receive beam pattern improvement and correlation coefficients of transmitted waveforms is investigated. The signal to interference and noise ratio varying with correlation coefficients in range-Doppler matched processing is defined and analysed. Furthermore, Cramer–Rao bound for target direction of arrival estimation and target detection probability in the Neyman–Pearson criteria are derived when transmitting correlated waveforms. It is shown that the MIMO radar detection and localisation performance is much dependent with the correlation level of transmitted waveforms, which can be quite useful for MIMO radar orthogonal waveform design. Numerical simulation validates the theoretical analysis.

Use of multiple transmit and receive antennas have become a popular research area in radar community after the success of the same concept in communication. It is shown by Fishler et al. that multi-input multi-output (MIMO) radar has considerable advantages compared to traditional radar and phased array radar systems. In this paper, detection performance of MIMO radar using Neyman-Pearson detector is investigated in K-distributed sea clutter for a practical scenario. Also, spikiness of K-distributed MIMO radar clutter is discussed with respect to the number of nodes.

Based on the array architecture of multiple transmitting/receiving antennas, Multi-Input Multi-Output (MIMO) radar provides a new mechanism for radar imaging technology. In order to explore the processing approach to this imaging mechanism, the two dimensional (2D) imaging model of MIMO radar is established first, and the spatial sampling ability is analyzed from the concept of spatial convolution of the antenna elements. The target spatial spectral filling format of MIMO radar with monochromatic transmitting signal is described. High-resolution imaging capability of MIMO radar is analyzed according to spatial spectral coverage and the corresponding imaging algorithm is presented. Finally, field imaging experiment is used to demonstrate the superior imaging performance of MIMO radar.

New correlated MIMO radar covariance matrix design with low side lobe levels and much lower complexity

This letter discusses the problem of direction of departure (DOD) and direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar, and derives a reduced-dimension multiple signal classification (MUSIC) algorithm therein. The proposed algorithm, which only requires one-dimension search, can avoid the high computational cost within two-dimension MUSIC (2D-MUSIC) algorithm. We illustrate that the algorithm has better performance ESPRIT algorithm, and has very close performance to 2D-MUSIC algorithm. Further our algorithm requires no pair matching. Simulation results verify the usefulness of our algorithm.

A novel target detection algorithm for large array multi-input multi-output (MIMO) radar in spatially correlated noise is proposed in this paper using canonical correlation technique (CCT). In the signal model, two separate sub-arrays are employed as the receive array of a transmit diversity MIMO radar system. Assume that the elementary noise in each sub-array has spatial correlation, and the number of receive elements is large and grows as the same rate with the snapshots. The detection statistics is constructed based on the generalized likelihood ratio test (GLRT) criterion and the sample canonical correlation coefficient between the two subarrays. The expression of decision threshold is derived via the Tracy-Widom distribution of order 2 in random matrix theory. The simulation results show that the detection performance of the proposed algorithm is better than that of the conventional condition number (CN)-based algorithm in the presence of spatially correlated noise and large array.

Multi-input multi-output (MIMO) radar systems have taken considerable attention among radar community in recent years. As stated in some publications MIMO radars have serious performance advantages compared to single-input single-output (SISO) radars. Although MIMO radars perform well theoretically, they have some practical problems. One of these problems is the data transmission rate required by MIMO radars. Quantization directly affects the amount of data to be transmitted. In this paper effects of quantization on MIMO radar performance is covered.

This paper applies wavelet transform (WT) on Orthogonal Frequency Division Multiplexing (OFDM) and single carrier (SC) digital signals twice (WT-T) to extract the transient characteristics of them, and then by using the transient characteristics in WT-T domain, it is easy to identify the two types of signals. The simulations show that the proposed identification algorithms can obtain good performances in low signal to noise ratio (SNR) and multipath Rayleigh fading channel. In addition, the effects of sample rate and symbol rate on the identification algorithms are analyzed and simulated. To obtain the best performances of the identification algorithms, sample rate is set to be equal to 2.4 times of carrier frequency approximately, therefor, the difference of characteristics between OFDM and SC signals reaches maximum, while OFDM and SC signals can be well separated if only the symbol rate is greater than 20 kHz.

This thesis presents two original ontributions on orthogonal frequency division multiplexing (OFDM). The first is a thorough investigation of the error performance and channel capacity of asymmetrically clipped optical OFDM (ACO-OFDM). ACO-OFDM is a modulation scheme designed specifically for optical communications. The second concerns the use of multiple-input multiple-output (MIMO) OFDM in radio frequency (RF) systems. A new scheme which uses polynomial cancellation coding (PCC) OFDM with time offsets is proposed. This new scheme is robust to both carrier frequency offset (CFO) and channel estimation errors. OFDM has been used extensively to reduce the effect of dispersion in wired and wireless RF systems. Although dispersion is also a problem in optical wireless systems, OFDM has not until recently been considered for use in these. This is because optical wireless systems use intensity modulation (IM) and so the transmitted signals must be nonnegative and as a result conventional OFDM signals which are bipolar cannot be used directly. ACO-OFDM and DC biased optical OFDM (DCO-OFDM) are two non-negative forms of OFDM developed for optical systems. Both are robust to ISI but ACO-OFDM is in most cases much more power efficient. In this thesis results are presented for the performance of ACO-OFDM, DCO-OFDM and conventional optical modulation schemes such as on-off keying (OOK) and pulse position modulation (PPM) for both dispersive and non-dispersive channels. These show that ACO-OFDM is more tolerant to dispersion and requires less optical power than the other modulation schemes. To investigate the theoretical limits of an ACO-OFDM system, closed form analytical expressions for the channel capacity of ACO-OFDM are derived both for a flat channel and for representative dispersive optical wireless channels. The capacity of ACO-OFDM cannot be compared with the general case of an intensity modulated signal, because no general solution for this has yet been found. Instead the mutual information of an ACO-OFDM signal is calculated and compared with two other signal distributions: an exponential distribution and a clipped-Gaussian distribution. The combination of OFDM and MIMO has been used in several radio standards. However, MIMO OFDM systems like single-input single-output (SISO) OFDM systems are very sensitive to CFO. An improved MIMO PCC OFDM system is proposed in this thesis. In this system, the signals transmitted from different antennae have different time offsets. At the receiver, OFDM symbols are demodulated by using each of these time offsets in a matched detection window. This system shows better performance than a MIMO PCC OFDM system without time offsets in two cases: when there are channel estimation errors and in MIMO systems with more transmit antennae than receive antennae.

We propose the use of compressive sensing (CS) in the context of a multi-input multioutput (MIMO) radar system that is implemented by a small scale network. Each receive node compressively samples the incoming signal, and forwards a small number of samples to a fusion center. At the fusion center, all received data are jointly processed to extract information on the potential targets via the CS approach. Since CS-based MIMO radar would require many fewer measurements than conventional MIMO radar for reliable target detection, there would be power savings during the data transmission to the fusion center, which would prolong the life of the wireless network. First, we propose a direction of arrival (DOA)-Doppler estimation approach. Assuming that the targets are sparsely located in the DOA-Doppler space, based on the samples forwarded by the receive nodes, the fusion center formulates an ℓ1-optimization problem, the solution of which yields the target DOA-Doppler information. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than required by conventional approaches. Second, we propose the use of step frequency to CS-based MIMO radar, which enables high range resolution, while transmitting narrowband pulses. For slowly moving targets, a novel approach is proposed that achieves significant complexity reduction by successively estimating angle-range and Doppler in a decoupled fashion and by employing initial estimates to further reduce the search space. Numerical results show that the achieved complexity reduction does not hurt resolution. Finally, we investigate optimal designs for the measurement matrix that is used to linearly compress the received signal. One optimality criterion amounts to decorrelating the bases that span the sparse space of the incoming signal and simultaneously enhancing signal-to-interference ratio (SIR). Another criterion targets SIRimprovement only. It is shown via simulations that, in certain cases, the measurement matrices obtained based on the aforementioned criteria can improve detection accuracy as compared to the typically used Gaussian random measurement matrix.

Multi-level modulation on orthogonal frequency division multiplexing (OFDM) signals is experimentally demonstrated by an integrated silicon Mach-Zehnder modulator. The measured bit error rate is well below the forward error correction (FEC) threshold.

For target localization with radar, time of arrival (TOA), angle of arrival (AOA) and frequency of arrival (FOA) informations can be used in cooperation. In general, TOA information is enough to localize a target. Moreover, if the target velocity should be estimated, the target velocity is able to estimated by using doppler frequency. In this paper, the Cramer-Rao Bound (CRB) is shown for Multi Input, Multi Output (MIMO) radar with widely separated antennas case. CRB's are compared for different targets and transmitter-receiver configurations.

We investigate a novel dispersion compensating technique in double sideband (DSB) modulated and directed-detected (DD) passive optical network (PON) systems using super-Nyquist image induced aliasing. We show that diversity is introduced to the higher frequency components by deliberate aliasing using the super-Nyquist images. We then propose to use fractional sampling and per-subcarrier maximum ratio combining (MRC) to harvest this diversity. We evaluate the performance of conventional orthogonal frequency division multiplexing (OFDM) signals along with discrete Fourier transform spread (DFT-S) OFDM and code-division multiplexing OFDM (CDM-OFDM) signals using the proposed scheme. The results show that the DFT-S OFDM signal has the best performance due to spectrum spreading and its superior peak-to-average power ratio (PAPR). By using the proposed scheme, the reach of a 10-GHz bandwidth QPSK modulated OFDM-PON can be extended to around 90 km. We also experimentally show that the achievable data rate of the OFDM signals can be effectively increased using the proposed scheme when adaptive bit loading is applied, depending on the transmission distance. A 10.5% and 5.2% increase in the achievable bit rate can be obtained for DSB modulated OFDM-PONs in 48.3-km and 83.2-km standard single mode fiber (SSMF) transmission cases, respectively, without any modification on the transmitter. A 40-Gb/s OFDM transmission over 83.2-km SSMF is successfully demonstrated.

When Multi-Input Multi-Output (MIMO) radar and communication transceivers are co-existing and operating simultaneously in the same frequency band, interference can be managed by designing signal spaces that facilitate spectrum sharing. In this paper, a spatial precoder-decoder design based on Interference Alignment (IA) is proposed assuming that an interference channel is shared by K c communication users and K r radar users. In order to find an IA based precoder-decoder solution guaranteeing desired multiplexing gain or diversity order, the design problem is formulated using a rank minimization criterion with rank constraint for the communication subsystem and rank minimization criterion with l 0 norm constraint for the radar, respectively. To deal with the non-convex nature of the optimization problem, we relax the problem by using nuclear norm. A generalized likelihood ratio test for target detection and a maximum likelihood estimator for target direction parameter are derived. The performance of the proposed IA based precoder-decoder design is analyzed using the GLRT detector and the ML estimator for MIMO radar. Analytical and simulation results show that radar detection performance is similar to the interference-free case with desired diversity order if the decoder matrix is semi-unitary and IA is perfect.