Earticle

This study proposes a method to reduce the phase error of the received signal to detect the object bearing. The phase shift of the received signal occurs due to the multipath of the signal by natural structure or artificial structures. When detecting the direction of the object using radio waves, the phase of the received signal cannot be accurately detected because of the phase bearing error in the object detection direction. The object detection direction estimation depends on the phase difference, antenna installation distance, signal source wavelength, frequency band and bearing angle. This study reduces the error of the phase bearing by using the phase delay of the relative phase difference for the signals incident on the two antennas. Through simulation, we analyzed the object direction detection performance of the proposed method and the existing method. Three targets are detected from the [−15°,0°,15°] direction. The existing method detects the target at [−13°,3°,17°], and the proposed method detects the at [−15°,0°,15°]. As a result of the simulation, the target detection direction of the proposed method is improved by 2 degrees compared to the existing method.

We study a method for removing interference and noise to estimate target range information accurately. The transmitted signal is mixed with interference and nois signal before being received. To accurately extract the desired information signal at the receiver, it is essential to eliminate these unwanted signals. This study proposes an algorithm that first obatins range information using the first FFT and then extracts the target range by calculating Doppler information with second FFT. This approach enhances target estimation accuracy. All FFT operations improve the signal-to-noise ratio through coherent intergration. The singal processing after the second FFT is similar to that of a pulse Dopppler radar. However, FFT distortion may occur due to the quantization effect caused by the saturation of the input signal during digital conversion, potentially degrading FMCW performance. To mitigatge this issue, real-time Augomatic Gaing Control is applied. The target range estimation of the proposed and existing methods is analyzed through simulation. The proposed method accurately estimates target range information, while the existing method exhibits estimation errors. The results show that the proposed method improves estimation accuracy by approximately 10% compared to the existing method.

This paper introduces a signal processing technique for discrimination of missile target. In order to detect and discriminate the target, a seeker radar makes use of chirp waveform and stretch processing to generate high resolution range profiles(HRRPs). RELAX(relaxation) algorithm, which is one of the spectral estimation techniques, was used to find scattering centers of a missile from HRRP. From the information on the distribution of one-dimensional(1-D) scattering centers on a target, we can discriminate the target without noise.

The FMCW(Frequency Modulation Continuous Wave) radar possesses range-velocity ambiguity to identify the correct combination of beat frequencies for each target in the multi-target situation. It can lead to ghost targets and missing targets, and it can reduce the detection probability. In this pap er, we propose an effective identification algorithm for the correct pairs of beat frequencies and the signal processing hardware architecture to effectively support the algorithm. First, using the correlation of the detected up- and down-beat frequencies and Doppler frequencies, the possible combinations are determined. Then, final pairing algorithm is completed with the power spectrum density of the correlated up- and down-beat frequencies. The proposed hardware processor has the basic architecture consisting of beat-frequency registers, pairing table memory, and decision unit. This method will be useful to improve the radar detection probability and reduce the false alarm rate.

무선 센서 네트워크에서 이동하는 표적의 위치를 추정하기 위한 연구는 센서 노드의 에너지가 제한 되어 있어 센서 노드 상호간의 협력적인 신호처리 기법이 필수적이다. 기존의 무선 센서 네트워크에서 이동 표적의 위치를 추정하는 방법은 각 센서 노드에서 이동 표적으로부터 수신된 신호를 이용해 수신신호강도, 잡음제거, 압축 등의 신호처리를 수행하고 기지국으로 전송하는 형태이다. 이런 기존의 기법은 애드 호크 방법의 무선 센서 네트워크에는 적용이 어렵고, 각 센서 노드에서 신호처리 및 통신에 의한 에너지 소모가 크기 때문에 무선 센서 네트워크의 생존 시간이 짧아지게 된다. 본 논문에서는 웨이블릿 기반의 무선 센서 네트워크의 협력적 신호 처리 방법을 제안한다. 제안된 방법은 웨이블릿 변환을 이용한 센서노드에서의 에너지 효율적 특징추출을 수행하고 각 센서 노드간의 특징 전송을 통해 표적의 위치를 추정한다.

Time of difference of arrival (TDOA) method using passive sonar sensor array has normally been used to estimate the location of a concealed moving target in underwater environment. Particle filter has been introduced for effective target estimation for non-Gaussian and nonlinear systems. In this paper, we propose a GPU-based acceleration of target position estimation using particle filter and propose efficient embedded system and software architecture. For the TDOA measurement from the passive sonar sensor, we use the generalized cross correlation phase transform (GCC-PHAT) method to obtain the correlation coefficient of the signal using FFT and we try to accelerate the calculation of GCC-PHAT based TDOA measurements using FFT with GPU CUDA. We also propose parallelization method of the target position estimation algorithm using the GPU CUDA to update the state of each particle for the target position estimation using the measured values. The target estimation algorithm was verified using Matlab and implemented using GPU CUDA. Then, we realized the proposed signal processing acceleration system using NVIDIA Jetson TX1 as the target board to analyze in terms of the execution time. The execution time of the algorithm is reduced by 55% to the CPU standalone-operation on the target board. Experiment results show that the proposed architecture is a feasible solution in terms of high-performance and area-efficient architecture.

In this paper, we propose a signal processing board suitable for a semi-active laser tracking to detect an optical signal generated from the laser target designator by applying an analog trigger signal, the quadrant photodetector and a high speed ADC(analog-digital converter) sampling technique. We improved the stability by applying the averaging method to minimize the measurement error of a gaussian pulse. To evaluate the performances of the proposed methods, we implemented a prototype board and performed experiments. As a result, we implemented a frequency counter with an error 14.9ns in 50ms. PRF error code has a stability of less than 1.5% compared to the NATO standard. Applying the three point averaging method to ADC sampling, the stability of 28% in X-axis and 22% in Y-axis than one point sampling was improved.