Abstract
To improve the detection efficiency of a long-distance dim point target based on dynamic programming (DP), this paper proposes a multi-frame target detection algorithm based on a merit function filtering DP ring (MFF-DPR). First, to reduce the influence of noise on the pixel state estimation results, a second-order DP named the MFF-DP is proposed. The current states of pixels on an image plane are estimated by maximizing the addition of the merit functions of the previous two frames and the observation data of the current frame. In addition, to suppress the diffusion of the merit function, the sequential and reverse observation data are connected in a head-to-tail manner to form a ring structure. The MFF-DP is applied to the ring structure, and the merit function of the MFF-DPR is obtained by averaging the merit functions of the sequential and reverse MFF-DPs. Finally, the target trajectory is obtained by correlating the extreme points of the merit functions of the MFF-DPR. The simulation and analysis results show that by merely adding a ring structure, the detection probability of the traditional DP can be improved by up to 40% when detecting point targets under the SNR of 1.8. The point target detection algorithm based on the MFF-DPR can achieve significantly better performance in point target detection compared with the traditional DPs with or without a ring structure. The proposed algorithm is suitable for radars and infrared point target detection systems.
Highlights
Accepted: 19 January 2022As a very important technology in the field of radar or infrared systems, point target detection has been widely studied, but its development has still been limited by certain challenges
Taking the MFF-dynamic programming (DP) as an example, this paper provides the steps of the the corresponding DP ring (DPR) algorithm, i.e., the merit function filtering DP ring (MFF-DPR) algorithm, as shown in Algori corresponding DPR algorithm, i.e., the MFF-DPR algorithm, as shown in Algorithm 1
The merit function of the MFF-DPR IΩ can be obtained by averaging merit functions of theThe sequential and reverse
Summary
As a very important technology in the field of radar or infrared systems, point target detection has been widely studied, but its development has still been limited by certain challenges. The energy accumulation-based algorithms [12,13] use the gray accumulation value of each stage of a target as a merit function, which simplifies the iteration steps. Unlike the traditional second-order DP, in the MFF-DP, the current states of pixels on an image plane are estimated by maximizing the addition of the merit functions of the previous two frames and the observation data of the current frame. In this way, direct involvement of the observed data in the state transition decision is avoided, reducing the influence of noise on the state estimation of pixels under the condition of a low SNR.
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