The final goal of the present project is to develop a ship detection and identification system by integrating spaceborne synthetic aperture radar (SAR), ground-based maritime radar and automatic identification system (AIS); and this article presents the results of the first phase experiments and current status toward achieving this goal. The data acquired by the Phased Array L-band SAR (PALSAR) on board of the Advanced Land Observing Satellite (ALOS) were used as SAR data, and X-band maritime radar including AIS were used as a ground-based system. The work is divided into two experimental phases. The first phase is to examine the ability of PALSAR to detect ships whose sizes are comparable with the SAR resolution cells, and the second is to incorporate the PALSAR data with those acquired by the ground-based radar with AIS. For the experiments in the first phase, we deployed three small fishing boats whose lengths ranged from approximately 8 m to 15 m in the Tosa Bay in Kochi, Japan in 2006. The experiments were carried out for four observation PALSAR modes: FBS (Fine Beam Single) 34.3, FBS 21.5, FBD (Fine Beam Double) 41.5, and PLR (PoLaRimetric) 20.5, where the numbers in each modes represent the off-nadir angles. For extracting the boats from the PALSAR images, five algorithms were considered, including amplitude-based, CFAR (Constant False Alarm Rate), MLCC (Multi-Look Cross-Correlation), CCF (Cross-Correlation Function) of HH- and HV-polarization amplitudes, and polarimetric analyses. This paper summarizes the results of the first phase experiments; the summary of the integrated system in the second phase will be reported in the near future.

A highly integrated monolithic Multi-Service Transport Platform (MSTP) ASIC MSEOSX8-6 incorporating more than 26M transistors has been fabricated with 0.18 µm CMOS technology. The chip is a powerful monolithic MSTP ASIC that supports RPR applications and serves as a generic building block for MSTP network. To accelerate the chip design, we devise a novel methodology called Embedded Reduced Self-Tester (ERST), which integrates the reduced self-tester structure into the chip to shorten the duration of dynamic simulation. Moreover, we divide the design into 12 smaller Hierarchical Layout Blocks (HLB) to enable parallel layout. Resultantly, the whole design has been completed in 5 months, which saves at least 80% of the design cycle in all.

In this paper, we analyze the coexistence issues of M-WiMAX TDD and WCDMA FDD systems. Smart antenna techniques are applied to mitigate the performance loss induced by adjacent channel interference (ACI) in the scenarios where performance is heavily degraded. In addition, an ACI model is proposed to capture the effect of transmit beamforming at the M-WiMAX base station. Furthermore, a MCS-based throughput analysis is proposed, to jointly consider the effects of ACI, system packet error rate requirement, and the available modulation and coding schemes, which is not possible by using the conventional Shannon equation based analysis. From the results, we find that the proposed MCS-based analysis method is quite suitable to analyze the system theoretical throughput in a practical manner.

In this letter, an effective algorithm is proposed to improve the performance of relay enhanced cellular networks, which is to allocate appropriate resources to each access point with quality of service constraint. First we derive the ergodic rate for backhaul link based on a poison point process model, and then allocate resources to each link according to the quality of service requirements and ergodic rate of links. Numerical results show that the proposed algorithm can not only improve system throughput but also improve the rate distribution of user equipment.

The GMM-UBM framework has been proved to be one of the most effective approaches to the automatic speaker verification (ASV) task in recent years. In this letter, we first propose an approximate decision function of traditional GMM-UBM, from which it is shown that the contribution to classification of each Gaussian component is equally important. However, research in speaker perception shows that a different speech sound unit defined by Gaussian component makes a different contribution to speaker verification. This motivates us to emphasize some sound units which have discriminability between speakers while de-emphasize the speech sound units which contain little information for speaker verification. Experiments on 2006 NIST SRE core task show that the proposed approach outperforms traditional GMM-UBM approach in classification accuracy.

In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.

A novel conjugate unitary ESPRIT (CU-ESPRIT) algorithm for the joint direction of departure (DOD), and direction of arrival (DOA), estimation in a bistatic MIMO radar is proposed. A new virtual array is formed by using the properties of noncircular signals, and the properties of the centro-Hermitian matrix are employed to convert the complex-valued data matrix into a real-valued data matrix. Then the real-valued rotational invariance properties of the new virtual array are determined to estimate DODs and DOAs, which are paired automatically. The proposed method provides better angle estimation performance and detects more targets owing to double number of MIMO virtual array elements. Simulation results are presented to verify the effectiveness of the proposed algorithm.

The analytic expressions of lightning electromagnetic fields generated by tortuous channel with an inclined lower section are obtained by decomposing the current infinitesimal and solving Maxwell's equations. By using the transmission line model and pulse function to express the channel-base current, the influence of length and tilt angle of the oblique part on lightning electromagnetic fields as well as the distribution laws of electromagnetic fields for different azimuth angles are analyzed. The results show that the electromagnetic fields in near area are mainly determined by the lower section of the tortuous discharge channel, and the peak values of electromagnetic fields in different field regions will increase with the increasing of the length of the lower section when L1 is shorter than the distance that return-stroke speed multiplied by peak time. Whereas the length of the lower section is longer than the distance that return-stroke speed multiplied by peak time, the waveforms of electromagnetic fields will overlap each other and won't be influenced by oblique part length of the discharge channel before the return-stroke current arrives at the inflection point. Moreover, the peak values of electromagnetic fields will decrease with the increase of tilt angle (the azimuth angle φ = 2π/3) and azimuth angle, and the impact of channel geometry on the electromagnetic field strengthens with the distance.

A 2.45-GHz-band small passive radio-frequency identification (RFID) tag consists of a small loop antenna and chip, and its size is several millimeters. Because of the tag's poor impedance-matching characteristic and radiation efficiency, an ordinary reader has difficulty reading it. We propose a new technique for reading the tag that involves installing a square half-wavelength meander-line conductor on the reader as an adapter and placing the adapter in the vicinity of the tag, and verify the effectiveness of the technique by simulation and experiment. Moreover, characteristics of simultaneous read of the small RFID tags by the proposed reading technique are revealed by simulation and experimental results.

We have developed a capacitance sensor of frequency modulation for integrated touchpanels using amorphous In-Sn-Zn-O (α-ITZO) thin-film transistors (TFTs). This capacitance sensor consists of a ring oscillator, whose one stage is replaced by a reset transistor, sensing transistor, and sensing electrode. The sensing electrode is prepared as one terminal to form a sensing capacitor when the other terminal is added by a finger. The ring oscillator consists of pseudo CMOS inverters. We confirm that the oscillation frequency changes when the other terminal is added. This result suggests that this capacitance sensor can be applied to integrated touchpanels on flatpanel displays.

An improved iterative minimum mean-squared error (MMSE) channel estimation method is proposed for joint coding and precoding OFDM systems. Compared with the traditional simplified estimator, the proposed scheme provides higher estimation quality with slight complexity increment at low signal-to-noise ratio (SNR) values. The performance of the iterative receiver including the proposed estimator approaches that of the perfect MMSE estimator without any simplification.

With the rapid development of technology and economy, the number of cars is increasing rapidly, which brings a series of traffic problems. To solve these traffic problems, the development of intelligent transportation systems are accelerated in many cities. While vehicles and their detailed information detection are great significance to the development of urban intelligent transportation system, the traditional vehicle detection algorithm is not satisfactory in the case of complex environment and high real-time requirement. The vehicle detection algorithm based on motion information is unable to detect the stationary vehicles in video. At present, the application of deep learning method in the task of target detection effectively improves the existing problems in traditional algorithms. However, there are few dataset for vehicles detailed information, i.e. driver, car inspection sign, copilot, plate and vehicle object, which are key information for intelligent transportation. This paper constructs a deep learning dataset containing 10,000 representative images about vehicles and their key information detection. Then, the SSD (Single Shot MultiBox Detector) target detection algorithm is improved and the improved algorithm is applied to the video surveillance system. The detection accuracy of small targets is improved by adding deconvolution modules to the detection network. The experimental results show that the proposed method can detect the vehicle, driver, car inspection sign, copilot and plate, which are vehicle key information, at the same time, and the improved algorithm in this paper has achieved better results in the accuracy and real-time performance of video surveillance than the SSD algorithm.

Z-complementary pairs (ZCPs) were proposed by Fan et al. to make up for the scarcity of Golay complementary pairs. A ZCP of odd length N is called Z-optimal if its zero correlation zone width can achieve the maximum value (N + 1)/2. In this letter, inserting three elements to a GCP of length L, or deleting a point of a GCP of length L, we propose two constructions of Z-optimal ZCPs with length L + 3 and L - 1, where L=2α 10β 26γ, α ≥ 1, β ≥ 0, γ ≥ 0 are integers. The proposed constructions generate ZCPs with new lengths which cannot be produced by earlier ones.

In this letter, the performance improvement by the deployment of multiple antennas in cognitive radio systems is studied from a system-level view. The term opportunistic spectrum efficiency (OSE) is defined as the performance metric to evaluate the spectrum opportunities that can actually be exploited by the secondary user (SU). By applying a simple energy combining detector, we show that deploying multiple antennas at the SU transceiver can improve the maximum achievable OSE significantly. Numerical results also reveal that the improvement comes from the reduction of both the detection overhead and the false alarm probability.

The electromagnetic environment is increasingly complex and changeable, and radar needs to meet the execution requirements of various tasks. Modern radars should improve their intelligence level and have the ability to learn independently in dynamic countermeasures. It can make the radar countermeasure strategy change from the traditional fixed anti-interference strategy to dynamically and independently implementing an efficient anti-interference strategy. Aiming at the performance optimization of target tracking in the scene where multiple signals coexist, we propose a countermeasure method of cognitive radar based on a deep Q-learning network. In this paper, we analyze the tracking performance of this method and the Markov Decision Process under the triangular frequency sweeping interference, respectively. The simulation results show that reinforcement learning has substantial autonomy and adaptability for solving such problems.

AlphaSeq is a new paradigm to design sequencess with desired properties based on deep reinforcement learning (DRL). In this work, we propose a new metric function and a new reward function, to design an improved version of AlphaSeq. We show analytically and also through numerical simulations that the proposed algorithm can discover sequence sets with preferable properties faster than that of the previous algorithm.

A low-complexity method for angle estimation in Multiple-input multiple-output radar (MIMO) radar is presented. In this approach, the signal subspace can be spanned by the orthogonal vectors which are obtained by Multi-stage Wiener Filter (MSWF), then the ESPRIT method can be used to estimate direction of departures (DODs) and direction of arrivals (DOAs). Compared with the conventional ESPRIT algorithm, the proposed method does not involve estimation of the covariance matrix and its eigen-decomposition, which alleviates remarkably the computational complexity. Moreover, the proposed method achieves the similar angle estimation performance. Simulation results are presented to verify the efficiency of the proposed method.

In this paper, the Getis statistic is applied to ALOS- PALSAR (Advanced Land Ovserving Satellite-Phased Array L-band Synthetic Aperture Radar) images for assessing the building damage caused by the Wenchuan earthquake in 2008. As a proposed image analysis, a simulated building image using mapping and projection algorithm is first presented for analysis of the Getis statistic. The results show the high accuracy of the assessment of the proposed approach. The Getis statistic is then applied to two ALOS-PALSAR images acquired before and after the Wenchuan earthquake to assess the level of building damage. Results of the Getis statistic show that the damage level is approximately 81%.

In spectrum-sharing systems where the secondary user (SU) opportunistically accesses the primary user (PU)'s licensed channel, the SU should satisfy both the transmit power constraint of the SU transmitter and the received power constraint at the PU receiver. This letter studies the ergodic capacity of spectrum-sharing systems in fading channels. The ergodic capacity expression along with the optimal power allocation scheme is derived considering both the average transmit and received power constraints. The capacity function in terms of the two power constraints is found to be divided into transmit power limited region, received power limited region and dual limited region. Numerical results in Rayleigh fading channels are presented to verify our analysis.

In this paper, a novel approach for central angle estimation of coherently distributed targets that utilizes electric vector sensors in bistatic MIMO radar is proposed. First, the coherently distributed targets signal model in bistatic MIMO radar that equipped with electric vector sensors is reconstructed. The Hadamard product rotation invariance property of the coherently distributed targets' steering vectors is found to get the initial estimation of direction of departure (DOD). 1-D MUSIC is then used to estimate the accurate central angles of direction of arrival (DOA) and DOD. The proposed method can estimate the central angles of DOA and DOD efficiently and accurately without pairing even in the situation where the angular signal distribution functions are unknown. Our method has better performance than Guo's algorithm. Numerical results verify the improvement and performance of the proposed algorithm.