更新：1、kalman_filter_init_2dots函数中量测噪声协方差矩阵R中R[1][0]赋值错误；

2、数据预处理中波位号判断规则修改；
3、数据预处理中增加点迹数量限制，避免超过数组上限；
4、Dot_Coh_TAS::dot_coh_tas_process中增加容器非空判断；
5、d_cal_with_doppler中计算雅可比矩阵改为用预测值计算；
6、tmp_track_to_trust_track中数组索引为负的问题修复；
7、tmp_track_to_trust_track中对容器push_back后在修改元素可能导致无法修改容器中的元素；
8、修改部分参数，适配机扫模式；

Signed-off-by: waiwaylee <waiwaylee@foxmail.com>

data_process_class_dll/data_process.cpp

@@ -18,7 +18,7 @@ int Data_Process::data_preprocess(struct DataRev    Data_Input[150])
 	//数据存入缓存区域 Data_buffer
 	if(Data_Input[0].point_type == 0)        //tws数据
 	{
-		data_num=Data_Input[0].Point_Sum;
+		data_num=min(Data_Input[0].Point_Sum, 150);
 		TAS_track_idx = Data_Input[0].TAS_track_index;
 		for (int i=0; i<data_num;i++)
 		{
@@ -42,7 +42,7 @@ int Data_Process::data_preprocess(struct DataRev    Data_Input[150])
 
 			Data_buffer.push_back(Data_buffer_temp);
 		}
-		if(Data_Input[0].Beam_index_aiz == 16)              //TWS
+		if(Data_Input[0].Beam_index_aiz % 16 == 0)              //TWS
 		{
 			 return 1;
 		}

data_process_class_dll/data_process_class_dll.h

@@ -16,6 +16,7 @@ struct DATA_PROCESS_CLASS_DLLSHARED_EXPORT DataRev
 	 float  Threshold;              //目标门限
 	 float  Snr;                    //目标信噪比
 	 float  RCS;                    //目标RCS
+	 float	Encoder_value;			//码盘值
 	 int    CPI_time;               //CPI时间  该波位无点迹输入时也需要给出当前时间
 	 int    Beam_index_azi_0;       //上一个cpi波位
 	 int    Beam_index_aiz;         //方位波位号（0-24）   该波位无输入点迹时 也需要给出当前波位

data_process_class_dll/data_process_class_dll.pro.user

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <!DOCTYPE QtCreatorProject>
-<!-- Written by QtCreator 4.0.2, 2026-06-25T15:53:21. -->
+<!-- Written by QtCreator 4.0.2, 2026-06-30T13:50:16. -->
 <qtcreator>
  <data>
   <variable>EnvironmentId</variable>

data_process_class_dll/dot_coh_tas.cpp

@@ -10,7 +10,9 @@ int Dot_Coh_TAS::dot_coh_tas_process(QVector <PointRecv>                *data_in
 									 QVector <PointRecv>                *point_recv_tas           //输出点迹
 									 )
 {
-
+	if (data_input->size() == 0) {
+		return 1;
+	}
 
 	for (int loop_of_point=0; loop_of_point<data_input->size()-1;loop_of_point++ )
 	{

data_process_class_dll/kalman.cpp

@@ -29,7 +29,7 @@ void kalman:: kalman_filter_init_2dots(double Z0[2], double Z1[2], double T,doub
 	R[0][0]=(pow(lambda_theta,-2)-2)*rho*rho*cos(theta)*cos(theta)+0.5*(rho*rho+SIGMA_R*SIGMA_R)*(1+lambda_theta1*cos(2*theta));
 	R[1][1]=(pow(lambda_theta,-2)-2)*rho*rho*sin(theta)*sin(theta)+0.5*(rho*rho+SIGMA_R*SIGMA_R)*(1-lambda_theta1*cos(2*theta));
 	R[0][1]=(pow(lambda_theta,-2)-2)*rho*rho*sin(theta)*cos(theta)+0.5*(rho*rho+SIGMA_R*SIGMA_R)*lambda_theta1*sin(2*theta);
-	R[1][0]=R[1][1];
+	R[1][0]=R[0][1];
 
 
 	P[0][0]=R[0][0];
@@ -358,10 +358,10 @@ double kalman:: d_cal_with_doppler(double F[6][6], double Q[6][6] , double Z[2],
 
 
 	//Z(k+1|k)
-	double x=X[0];
+	double x=X_pred[0];
-	double vx=X[1];
+	double vx=X_pred[1];
-	double y=X[3];
+	double y=X_pred[3];
-	double vy=X[4];
+	double vy=X_pred[4];
 	double h31=-y*(vx*y-vy*x)/((x*x+y*y)*sqrt(x*x+y*y));
 	double h32=-x/sqrt(x*x+y*y);
 	double h34=-x*(vy*x-vx*y)/((x*x+y*y)*sqrt(x*x+y*y));

data_process_class_dll/parameters.h

@@ -70,7 +70,7 @@
 //#define DATA_RATE_MIDDLE 1
 //#define DATA_RATE_FAR    1
 
-#define DATA_RATE_TAS 0.3
+#define DATA_RATE_TAS 0.33
 
 #define SIGMA_R    10.0         //测量误差
 #define SIGMA_A    0.02
@@ -109,9 +109,9 @@
 #define H_F_WIN_LEN 3
 
 
-#define TAS_QUEUE_LENGTH 4  //Tas调用的cpi数
+#define TAS_QUEUE_LENGTH 1  //Tas调用的cpi数
-#define MAX_TAS_NUM 4
+#define MAX_TAS_NUM 1
-#define T_TAS_PRED 0.7
+#define T_TAS_PRED 0.33
 
 #define UNCONF_TARGET 0
 

data_process_class_dll/track_init.cpp

@@ -694,7 +694,7 @@ void Track_Init::tmp_track_to_trust_track(QVector<Trust_Track>    *trust_track,
 					Direction_Angle=atan2(Track_to_start[i][j].X[3],Track_to_start[i][j].X[1]);
 					if(Direction_Angle<0)
 						Direction_Angle=Direction_Angle+2*PI;
-					Trust_Track_Output[*Trust_track_num_Output-1][j-1].Direction_Angle=Direction_Angle/PI*180;
+					Trust_Track_Output[*Trust_track_num_Output-1][j].Direction_Angle=Direction_Angle/PI*180;
 
 
 

data_process_class_dll/track_init_direct_tracking.cpp

@@ -370,13 +370,14 @@ void Track_Init_Direct_Tracking::tmp_track_to_trust_track(  QVector<Trust_Track>
 			memcpy(trust_track_tmp.P2, P, 6*6*sizeof(double));
 			memcpy(trust_track_tmp.X3, X, 6*sizeof(double));
 			memcpy(trust_track_tmp.P3, P, 6*6*sizeof(double));
-			(*trust_track).push_back(trust_track_tmp);
 
 			trust_track_tmp.pitch_num = (*Iter)[L-1].pitch_num;
 
 			std::memcpy(trust_track_tmp.speed_dim, (*Iter)[L-1].speed_dim, sizeof(trust_track_tmp.speed_dim));
 			std::memcpy(trust_track_tmp.range_dim, (*Iter)[L-1].range_dim, sizeof(trust_track_tmp.range_dim));
 
+			(*trust_track).push_back(trust_track_tmp);
+
 			//输出航迹更新信息
 			*Trust_track_num_Output=*Trust_track_num_Output+1;
 			for (int j=0;j<L;j++)