We propose a new fine Doppler frequency estimator using two fast Fourier transform (FFT) samples for pulse Doppler radar that offers highly sensitive detection and a high resolution of velocity. The procedure of fine Doppler frequency estimation is completed through coarse frequency estimation (CFE) and fine frequency estimation (FFE) steps. During the CFE step, the integer part of the Doppler frequency is obtained by processing the FFT, after which, during the FFE step, the fractional part is estimated using the relationship between the FFT peak and its nearest resultant value. Our simulation results show that the proposed estimator has better accuracy than Candan's estimator in terms of bias. The root mean square error (RMSE) of the proposed estimator has more than 1.4 time better accuracy than Candan's estimator under a 1,024-point FFT and a signal-to-noise ratio (SNR) of 10 dB. In addition, when the FFT size is increased from 512 to 2,048, the RMSE characteristics of the proposed estimator improve by more than two-fold.

In this paper, we propose a time and memory efficient Ultra Wide Band Short Range Radar (UWB SRR) system for measuring relative target velocities of up to 150km/hr. First, for the proposed detector, we select the required design parameters for good performance. The parameters are the number of coherent integrations, non-coherent integrations, and FFT points. The conventional detector uses a Fast Fourier Transform (FFT) to extract the range and velocity of the target simultaneously. Therefore, it requires high computation effort, high FFT processing time, and a huge amount of memory. However, the proposed pulse radar detector first decides the target range and then computes the target velocity using FFT sequentially for the decided range index. According to our theoretical and simulation analyses, the FFT processing time and the memory requirement are reduced compared to those of the conventional method. Finally, we show that the detection performance of the proposed detector is superior to that of the conventional detector in a background of Additive White Gaussian Noise (AWGN).

In automotive frequency modulated continuous wave (FMCW) radar based on multiple ramps with different slope, an effective pairing algorithm is required to simultaneously detect the target range and velocity. That is, as finding beat-frequencies intersecting at a single point of the range-Doppler map, we extract the range and velocity of a target. Unlike the ideal case, however, in a real radar system, even though multiple beat frequencies are originated from the same target, these beat frequencies have many different intersection values, resulting in mismatch pairing during the pairing step. Moreover, this problem also reduces the detection accuracy and the radar detection performance. In this study, we found that mismatch pairing is caused by the round-off errors of the range-beat frequency and Doppler frequency, as well as their various combinations in the discrete frequency domain. We also investigated the effect of mismatch pairing on detection performance, and proposed a new approach to minimize this problem. First, we propose integer and half-integer frequency position-based pairing method during extraction of the range and Doppler frequencies in each ramp to increase detection accuracy. Second, we propose a window-based pairing method to identify the same target from range-Doppler frequencies extracted in the first step. We also find the appropriate window size to overcome pairing mismatch. Finally, we propose the method to obtain a higher accuracy of range and velocity by weighting the values determined in one window. To verify the detection performance of the proposed method by comparison with the typical method, simulations were conducted. Then, in a real field test using the developed radar prototype, the detection probability of the proposed algorithm showed more than 60% improvement in comparison with the conventional method.

In this paper, we propose a memory-efficient structure for a pulse Doppler radar in order to reduce the hardware's complexity. The conventional pulse Doppler radar is computed by fast frequency transform (FFT) of all range cells in order to extract the velocity of targets. We observed that this method requires a huge amount of memory to perform the FFT processes for all of the range cells. Therefore, instead of detecting the velocity of all range cells, the proposed architecture extracts the velocity of the targets by using the cells related to the moving targets. According to our simulations and experiments, the detection performance of this proposed architecture is 93.5%, and the proposed structure can reduce the hardware's complexity by up to 66.2% compared with the conventional structure.